Role

As a member of our tight knit physical design team, you will perform synthesis, place and route of our most critical processing element blocks. You will be involved in all aspects of physical design and implementation. You will work closely with the RTL team and with full-chip integration of these blocks.

Skills & Qualifications

• 5+ years of physical design/verification experience.
• Strong knowledge of block level and full-chip physical verification methodology.
• Expert at optimizing for the best power/performance and area
• Experience with the complete physical design flow. Knowledge of Synopsys tool suite is a plus.
• Expert with ICV or Calibre tools resolving block and full-chip DRC and LVS issues.
• Expert with IR/EM analysis and resolution
• Good understanding of full chip floorplanning and integration.
• Strong ability in scripting languages like Tcl and Python. Ability to make flow enhancements.
• Demonstrated ability to work with RTL teams to optimize for physical design

Responsibilities

• Develop the system level AC, AC-DC and DC-DC power requirements for new products, including initial definition, concept design, detailed design and analysis, through final production and test
• Hands-on circuit design, modeling, and analysis for high power AC and DC systems
• Drive performance vs power analysis to enable meaningful product decisions, and support customer interaction including customer facilities reviews in advance of system shipments
• Specify, design, and oversee assembly of the lab bench environment to support product development and evaluation
• Ensure power subsystems and overall system meets safety and compliance requirements and support evaluation
• Engage effectively with power supply vendors to specify requirements and ensure on-time delivery of modules meeting specified performance requirements
• Work collaboratively with cross functional development team, including SW, ASIC, Systems, NPI Engineering and Supply Chain

Qualifications

• BS EE or equivalent engineering discipline
• 5+ years of experience in high power product development environment
• Proficiency with lab/test scripting SW (eg Python) and analytical SW tools is a must
• MS preferred
• Experience in IT, data center, or HPC development environments preferred

Responsibilities

• Lead pre-layout and post-layout simulation flow with a focus on high-speed interface and PDN, create simulation models and develop simulation methodology for SIPI design
• Lead SIPI validation methodology and develop detailed engineering test plans
• Model and optimize SI channel for PCBA, FPGA and ASIC on POD12 SE and SerDes interface standards
• Validate high speed interface and PDN impedance in lab to correlate simulation results and improve design flow
• Use simulation and lab data to support design troubleshooting and propose corrective actions, drive failure analysis, root cause efforts, and design of experiments to resolve problems
• Work with EE Board and Power design engineers, and ASIC design and verification engineers in collaborative cross functional teams to achieve project objectives
• Support multiple projects at the same time

Requirements

• MS EE or equivalent
• 5+ years of relevant SI/PI work experience in IT, HPC and/or AI hardware accelerator systems design

About The Role

As a member of our Compiler team, you will work with leaders from industry and academia to develop entirely new solutions for the toughest problems in AI compute. As deep neural network architectures evolve, they are becoming enormously parallel, and distributed. Compilers are needed to optimize the mappings of computation graphs to compute nodes. In this position, you will build the tools that generate distributed memory code from evolving intermediate representations.

Responsibilities

• Design and devise graph semantics, intermediate representations, and abstraction layers between high-level definitions (like MLIR) and low-level (LLVM IR) distributed code
• Use state-of-the-art parallelization and partitioning techniques to automate generation of distributed kernels
• Low-level optimization on a SIMD/tensor-aware architecture of compute nodes
• Identify, design and implement novel program analysis and optimization techniques
• Design and implement custom system tools (such as linkers) for architectures with massive number of compute nodes

Requirements

• Enrolled in the University of Toronto's PEY program with a degree in Computer Science, Computer Engineering, or other related disciplines
• High proficiency in programming using Python or C++
• Solid understanding of fundamental concepts related to system design, such as data structures, algorithms, and operating systems.
• Related experience or fundamental knowledge of compilers and distributed systems
• Familiarity with high-level parallel program analysis and optimization

Preferred

• LLVM compiler internals
• Polyhedral models
• Familiarity with HPC kernels and their optimization

About The Role

As a Kernel Engineer on our team, you will work with leaders from industry and academia at the intersection of hardware and software to develop state-of-the-art solutions for emerging problems in AI and HPC.

Our team of developers is responsible for the design, implementation, validation, and performance tuning of deep learning operations on highly parallel custom processors. We are developing a library of parallel and distributed algorithms to maximize hardware utilization and accelerate the training of deep neural networks to unprecedented speeds.

Responsibilities

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms
• Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system
• Using mathematical models and analysis to measure the software performance and inform design decisions
• Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries
• Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems

Requirements

• Enrolled within University of Toronto's PEY program with a degree in Computer Science, Computer Engineering, or any other related discipline
• Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture
• Skilled in C++ and Python programming languages
• Good knowledge of library and/or API development best practices
• Strong debugging skills and knowledge of debugging complex software stack

Preferred Skills

• Experience in kernel development and/or testing
• Familiarity with parallel algorithms and distributed memory systems
• Experience in programming accelerators such as GPUs and FPGAs
• Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch
• Familiarity with HPC kernels and their optimization

About The Role

As a Software Automation Engineer, you will use your knowledge of testing and testability to influence better software design, promote proper engineering practice, bug prevention strategies, testability, scalability, and other advanced quality concepts. The position will play a huge role in the quality of Cerebras software. We are looking for engineers that have a broad set of technical skills and who are ready to tackle the biggest at-scale problems in HW-based deep learning accelerators.

Responsibilities

• Write scripts to automate testing and create tools to allow easy development of software regression tests
• Help identify weak spots and potential customer pain points and drive the software organization towards customer focused quality metrics
• Implement creative ways to break software and identify potential problems
• Contribute to developing requirements specifications with a focus on developing verification tests

Requirements

• Enrolled in the University of Toronto's PEY program with a degree in Computer Science, Computer Engineering, or other related discipline
• Experience in developing automated tests for compute/machine learning or networking systems within a large-scale enterprise environment
• Ability to take responsibility for monitoring product development and usage at all levels with an end goal toward improving product quality
• Strong knowledge of software system design, C++ and Python

Preferred

• Strong software testing experience with a proven track record in scaling highly technical teams
• Knowledge of UNIX/Linux and Windows environments
• Knowledge of neural network architecture and ML/AI deep learning principles
• Prior experience in designing and developing test automation for HW systems involving ASICs or FPGAs
• Prior experience working with live hardware systems and debug tools operating in a real time environment such as networking devices or live computing systems

Responsibilities

• Create tools and design workflows that enable the development, training, and deployment of machine learning models on our new hardware system
• Map abstract computations expressed via third-party ML frameworks into representations that can then be compiled into highly optimized executables that target Cerebras’ system
• Develop connections between representations of existing deep learning frameworks -- such as TensorFlow, Caffe/2, MXNet, CNTK -- with our customized back-end
• Understand the runtime environments of existing frameworks and our backend, and develop an execution model connecting them together in a way that is seamless to the user

Requirements:

• Enrolled in the University of Toronto's PEY program with a degree in Computer Science, Computer Engineering, or other related disciplines
• Understanding of state-of-the-art deep learning model architectures and training protocols
• Direct experience with one ML framework internals (like TensorFlow, PyTorch, ONNX, etc) strongly preferred
• Strong Python and C++ development skills

Preferred:

• Good understanding of how to define custom layers and back-propagate through them
• Experience with supervised deep learning models such as RNNs and CNNs
• Experience in vertical such as computer vision, language modeling or speech recognition

About the role

As an applied machine learning engineer, you will take today’s state-of-the-art solutions in various verticals and adapt them to run on the new Cerebras system architecture. You will get to see how deep learning is being applied to some of the world’s most difficult problems today and help ML researchers in these fields to innovate more rapidly and in ways that are not currently possible on other hardware systems.

Responsibilities

• Familiar with state-of-the-art transformer architectures for language and vision model.
• Bring up new state-of-the art model on Cerebras System and function validation.
• Train a model to convergence, and hyper-parameter tuning.
• Optimize model code to run efficiently on Cerebras System.
• Explore new model architecture that take advantage of Cerebras unique capabilities.
• Develop new approaches for solving real world AI problems on various domains.

Requirements

• • Masters or PhD in Computer Science or related field
  • Familiarity with JAX/TensorFlow/PyTorch
  • Good understanding of how to define custom layers and back-propagate through them.
  • Experience with transformer deep learning models
  • Experience in vertical such as computer vision or language modeling
  • Experience with Large Language Models such as GPT family, Llama, BLooM.

About the Role

Cerebras is looking for an exceptional ML Solutions Engineer to work closely with our customers–leaders in industry and academia—on a diverse set of machine learning applications, both commercial and scientific. In this role, you will work with world-class domain experts to enable cutting-edge deep learning research with the Cerebras Wafer Scale Engine, the largest chip in the world dedicated for AI compute.

As the voice of the customer and part of the broader product team, you will work directly with the product management team to inform product requirements and shape the future of our product. This role requires a breadth of knowledge from understanding deep learning models and being familiar with recent advances in this area, to being experienced with ML frameworks, algorithmic debug/analysis, and performance modeling. The role will have an enormous impact on the speed at which we can deliver new types of deep learning solutions on our software/hardware platform and will influence the next generations of our software/hardware platform.

If you are passionate about driving the next generation of deep learning applications and want to lead these projects to impact use cases across verticals from Healthcare and Life Sciences, to Financial Services, to Media and Entertainment, to Manufacturing, to Technology, and more, then join our world-class Solutions Engineering team.

Responsibilities

• Work with our customers to understand their business and research use cases and the types of deep learning models they are interested in unlocking with Cerebras hardware
• Create high-level performance estimates for particular customer problems and help users understand how their workloads will be executed on the CS-2
• Write or directly adapt prototype PyTorch model code for customer use cases and be the first to bring up these new networks on the CS-2
• Run experiments with customer models on our system

Requirements

• BS or MS degree in Computer Science or related field
• 2+ years of related work experience as a software engineer
• Strong debugging skills
• Experience with debugging complex software stack and hardware systems
• Familiarity with recent deep learning models in computer vision, natural language processing, sequence modeling such as GPT, LLaMA, T5, Falcon, Bloom, Stable Diffusion, ResNet etc.
• Experience with Python/bash, TensorFlow or PyTorch
• Proactive, “do-it-yourself” attitude
• Curiosity, desire and ability to learn quickly and be involved in diverse work
• Ability to multitask effectively in a dynamic environment
• Strong analytical and problem solving skills
• Excellent verbal and written communications skills with the ability to effectively collaborate with customers, management and engineering

About the role

As an applied machine learning engineer, you will work on adapting state of the art deep learning (DL) models to run on our wafer scale system. This includes both functional validation and performance tuning of a variety of core models for applications like Natural Language Processing (NLP), Large Language Models (LLMs), Computer Vision (CV) and Graph Neural Networks (GNN).

As a member of the Cerebras engineering team you will be implementing models in popular DL frameworks like PyTorch and using insights into our hardware architecture to unlock to full potential of our chip. You will work on all aspects of the DL model pipeline including:

• Dataloader implementation and performance optimization
• Reference model implementation and functional validation
• Model convergence and hyper-parameters tuning
• Model customization to meet customer needs.
• Model architecture pathfinding.

This role will allow you to work closely with partner companies at the forefront of their fields across many industries. You will get to see how deep learning is being applied to some of the world’s most difficult problems today and help ML researchers in these fields to innovate more rapidly and in ways that are not currently possible on other hardware systems.

Responsibilities

• Analyze, implement, and optimize DL models for the WSE
• Functional and convergence of models on the WSE
• Work with engineering teams to optimize models for the Cerebras stack
• Support engineering teams in functional and performance scoping new models and layers
• Work with customers to optimize their models for the Cerebras stack.
• Develop new approaches for solving real world AI problems on various domains.

Requirements

• Bachelor's degree in engineering, science, or related field with 8+ years of experience
• Experience programming in modern language like Python or C++
• In-depth understanding of DL learning methods and model architectures
• Experience with DL frameworks like PyTorch, TensorFlow and JAX
• Familiar with state-of-the-art transformer architectures for language and vision model.
• Experience in model training and hyper-parameter tuning techniques.
• Familiar with different LLM downstream tasks and datasets.

Preferred Skills

• A deep passion for cutting edge artificial intelligence techniques
• Master's or PhD in engineering, science or related field
• Understanding of hardware architecture
• Experience programming accelerators like GPUs and FPGAs

Cerebras is developing a radically new chip and system to dramatically accelerate deep learning applications. Our system runs training and inference workloads orders of magnitude faster than contemporary machines, fundamentally changing the way ML researchers work and pursue AI innovation.

We are innovating at every level of the stack – from chip, to microcode, to power delivery and cooling, to new algorithms and network architectures at the cutting edge of ML research. Our fully-integrated system delivers unprecedented performance because it is built from the ground up for the deep learning workload.

Cerebras is building a team of exceptional people to work together on big problems. Join us!

About the Role

As an Inspection and Assembly Technician you will be essential in our drive for innovation. You will collaborate closely with our engineering teams on our complex systems to develop solutions to support internal innovation and ensure high standards for quality.

Responsibilities

Responsibilities

• Work closely with our manufacturing partners and engineers through all stages of PCBA manufacturing including process development, build execution, and delivery
• Lead DFx initiatives and work closely with design engineering team to implement
• Work with supplier engineers for continuous process and quality improvements
• Support manufacturing and quality issues on the production line during builds
• Work with our CMs to document build parameters and details for traceability
• Lead root cause analysis and corrective action on process and quality issues
• Support weekly quality and manufacturing meetings with our CM partners
• Manage RMAs with our contract manufacturers and disposition product as required
• Escalate critical quality issues to engineering teams and management
• Identify and correct process, material, design and test program issues
• Research and recommend equipment and tools to improve Cerebras manufaturing and analytical capabilities
• Coordinate failure analysis activities with 3rd party labs

Requirements

• Bachelor's degree in Mechanical, Industrial, or Electrical Engineering or equivalent
  experience
• 5+ years of experience in PCBA manufacturing
• Experience with both Printed Circuit Board Assembly and Mechanical Assembly
• Knowledge of industry standards for PCBA – IPC610, JEDEC J-STD-001 and Test Methods
• Solid knowledge of PCBA drawing and schematics
• Experience with PLM systems such as Arena or Agile
• Strong communication and organization skills, with a logical approach to problem solving
• Able to work under pressure while managing competing demands and tight deadlines of multiple simultaneous projects and challenges

Preferred

• Familiarity with vapor phase soldering process and equipment

Location

• Sunnyvale, CA

About The Role

The system validation engineer role will focus on system-level design validation testing (DVT) and system integration validation. Nobody in the world has direct experience with our system. We are therefore looking for extraordinary individuals with outstanding track records for debugging, solving problems, and taking a product successfully to production. You will have the rewarding opportunity to be part of a team that works on state-of the art technology being applied to important problems such as Covid-19 research.

Responsibilities

• Work with the Design team to define system-level design validation testing (DVT) plan covering voltage, environmental, and cooling parameters, execute the test plan, and document the report
• Define the board and subassembly-level requirements for DVT teams and work with the Operations team to prepare components for building the DVT systems
• Determine software requirements for performing system-level DVT and work with system software teams to implement the tests
• Own the readiness of DVT chambers and external power and cooling infrastructure either through in-house development or working with external labs
• Maintain a set of stable hardware systems for software release four-corner regression testing
• Work with the Design team and System Software team to debug issues exposed in DVT and drive resolution

Skills & Qualifications

• Experience defining DVT and system integration test plans and writing test reports for high performance compute systems, covering electrical, mechanical, and thermal aspects
• Experience writing test scripts with Python, shell, and bash in Linux environment and effectively logging and analyzing a large amount of test results
• Excellent communication, planning, and coordination skills across Systems, Operations, and Software teams
• Familiarity with compute server architecture, high speed IO and system management IO interfaces, and power delivery
• Familiarity with liquid cooling and high voltage AC circuits
• Familiarity with test equipment such as oscilloscopes, protocol analyzers, time domain reflectometers, etc.
• Experience debugging system-level issues a plus

About The Role

We are seeking an exceptionally entrepreneurial senior marketer who is passionate about driving innovation and fostering creativity in a forward-thinking company.

As a key member of our organization, reporting directly to the CEO, you will spearhead marketing programs and projects, collaborating with executives and leading our storytelling efforts. You will work closely with cross-functional teams, including product management, sales, and executive leadership, to drive our messaging.

The ideal candidate is a skilled storyteller, using various marketing strategies to amplify our story in the market, nurture leads, and convert them into actionable sales opportunities. We seek someone proactive, ready to take swift and efficient action, with a strong desire to make a substantial impact.

Join us in our pursuit of creating an extraordinary marketing organization.

Responsibilities

• Responsible for marketing programs across domains: events, web, field marketing, and demand generation
• Create and own awareness and demand gen campaigns from initial planning stage to full execution across marketing channels (web, social, events)
• Ownership of company website and SEO & SEM plans to maximize reach and conversion
• Partner campaign execution while working with third parties such as customers and channels
• Leverage fluency in marketing analytics to continuously improve lead generation, nurture, and other program activities
• Manage marketing lead flow and nurture to effectively transition marketing leads to actionable sales leads

Requirements

• 9+ years in functional marketing roles across social media, website, webinar/events, and nurture campaigns
• 9+ years in marketing of highly technical product lines, preferably systems and/or semiconductors
• Extensive experience working with technical products, product management sales, and executives
• Extensive experience in agency management, working with multiple outside firms to align plans & responsibilities, and manage performance and output
• Outstanding verbal and written communication skills with technical and senior executive audiences
• Understanding of marketing analytics, including Google Analytics, website metrics, and social media data

Location

Sunnyvale, CA

About the role

As an applied machine learning engineer, you will take today’s state-of-the-art solutions in various verticals and adapt them to run on the new Cerebras system architecture. You will get to see how deep learning is being applied to some of the world’s most difficult problems today and help ML researchers in these fields to innovate more rapidly and in ways that are not currently possible on other hardware systems.

Responsibilities

• Familiar with state-of-the-art transformer architectures for language and vision model.
• Bring up new state-of-the art model on Cerebras System and function validation.
• Train a model to convergence, and hyper-parameter tuning.
• Optimize model code to run efficiently on Cerebras System.
• Explore new model architecture that take advantage of Cerebras unique capabilities.
• Develop new approaches for solving real world AI problems on various domains.

Requirements

• BS or Masters in Computer Science or related field
• Familiarity with JAX/TensorFlow/PyTorch
• Good understanding of how to define custom layers and back-propagate through them.
• Experience with transformer deep learning models
• Experience in vertical such as computer vision or language modeling
• Experience with Large Language Models such as GPT family, Llama, BLooM.

About The Role

As a Kernel Engineer on our team, you will work with leaders from industry and academia at the intersection of hardware and software to develop state-of-the-art solutions for emerging problems in AI and HPC.

Our team of developers is responsible for the design, implementation, validation, and performance tuning of deep learning operations on highly parallel custom processors. We are developing a library of parallel and distributed algorithms to maximize hardware utilization and accelerate the training of deep neural networks to unprecedented speeds.

Responsibilities

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms
• Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system
• Using mathematical models and analysis to measure the software performance and inform design decisions
• Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries
• Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems

Requirements

• Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields
• Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture
• Skilled in C++ and Python programming languages
• Good knowledge of library and/or API development best practices
• Strong debugging skills and knowledge of debugging complex software stack

Preferred Skills

• Experience in kernel development and/or testing
• Familiarity with parallel algorithms and distributed memory systems
• Experience in programming accelerators such as GPUs and FPGAs
• Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch
• Familiarity with HPC kernels and their optimization

About the role

As an applied machine learning engineer, you will take today’s state-of-the-art solutions in various verticals and adapt them to run on the new Cerebras system architecture. You will get to see how deep learning is being applied to some of the world’s most difficult problems today and help ML researchers in these fields to innovate more rapidly and in ways that are not currently possible on other hardware systems.

Responsibilities

• Familiar with state-of-the-art transformer architectures for language and vision model.
• Bring up new state-of-the art model on Cerebras System and function validation.
• Train a model to convergence, and hyper-parameter tuning.
• Optimize model code to run efficiently on Cerebras System.
• Explore new model architecture that take advantage of Cerebras unique capabilities.
• Develop new approaches for solving real world AI problems on various domains.

Requirements

• BS or Masters in Computer Science or related field
• Familiarity with JAX/TensorFlow/PyTorch
• Good understanding of how to define custom layers and back-propagate through them.
• Experience with transformer deep learning models
• Experience in vertical such as computer vision or language modeling
• Experience with Large Language Models such as GPT family, Llama, BLooM.

About the Role

As the Hardware Systems Product Manager, you will be responsible for developing and executing the product strategy for our high-performance AI computer systems. These cutting-edge systems are deployed in customer data centers or made available through remote access or cloud partners, enabling transformative AI and HPC workload performance. Working closely with hardware, systems, and ASIC engineering teams, you will play a key role in prioritizing and coordinating product development. Additionally, you will collaborate with customers who operate state-of-the-art computing facilities for HPC and AI compute, aiming to revolutionize AI and reshape the computing landscape. This is a senior or director level position, depending on candidate experience and fit.

Responsibilities

• Define, develop, maintain the hardware systems product roadmap
• Define and document system specifications and requirements
• Work directly with current and prospective customers to document and deeply understand market requirements for hardware systems, including data center space, power, cooling, and integration with adjacent systems
• Serve as a primary point of contact for hardware systems engineering to define roadmap and feature priorities, working as a partner to negotiate and co-define feature scope and staging
• Serve as a primary point of contact for partners in Marketing and Product Marketing to define and articulate our product story, value proposition, and differentiation
• Act as the voice of the user for internal product, engineering, and business leadership discussions, help facilitate product strategy decisions
• Inform hardware product decisions around feature prioritization, solutions, and functionality (e.g. for power, cooling, IO, physical system chassis)
• Work across product and engineering teams to translate product requirements into focused execution; help design and build our solution to accelerate customers’ AI research and development
• Act as the voice of the product for external engagements, supporting partners in Sales, customer accounts, conferences, and external events
• Work directly with customers to help map their most ambitious projects to CS hardware systems and enable their success

Requirements

• Bachelor’s or Master’s degree in computer science, electrical engineering, physics, mathematics, a related scientific/engineering discipline, or equivalent practical experience
• 4+ years product management experience, working with customers and engineering teams
• Direct product management experience with data center-deployed integrated hardware systems/appliances
• Demonstrated ability to work effectively with highly technical engineering teams
• Outstanding verbal and written communication skills

Preferred

• MBA or advanced degree such as PhD in science/engineering
• Machine learning and artificial intelligence domain knowledge with application experience
• Experience with hardware power, cooling, IO, and mechanical subsystems
• Experience with microprocessor architecture and ASIC development
• Experience with computer system engineering and data center infrastructure
• Experience with distributed systems, HPC system architecture, and applications
• Experience developing customer-facing technical proposals or responses to requests for information, proposals, or quotes
• Project and program management experience
• Prior startup or small company experience

The Role

We are seeking a dedicated leader to oversee our datacenter operations.

The key responsibilities of this role will encompass:

• • Cloud operations, capacity planning and build out of the Cerebras cloud.
  • Strategic vision - determining and executing the path forward and scale up of our data center to 500+ racks.
  • Capacity planning - optimizing resources and ensuring smooth operations and high uptime of the datacenter.
  • Adept leadership skills - effectively manage and lead a highly technical team, fostering collaboration and driving innovation.
  • Exceptional communication (written, verbal, documentation) with executive leadership and engineers is essential.

Skills & Qualifications

Scale

• • Experience operating a datacenter with 200-500 racks of equipment.
  • Experience with capacity planning (navigating a challenging supply market) from procurement to deployment.
  • Outstanding long-term planning and execution skills to carry our data center lifecycle planning.
  • Solid technical understanding of data center infrastructure, preferably including High Performance Compute data centers.

Pre-production

• • Experience operating prototype hardware in addition to production equipment

Leadership

• • Experience managing medium sized teams and building a team from scratch.
  • Orientated toward action at speed.
  • Able to prioritize and manage many work streams in parallel.
  • Adaptive to changes in a fast-paced and ambiguous environment, demonstrating ownership and a mission-focused attitude.
  • Collaborative approach and strong problem-solving skills to work with leaders across organizational and technical domains.

Communication

• • Excellent written and verbal interpersonal skills to lead effectively across cultures and geographies.
  • Communicate at all levels of a company from individual contributors, senior managers and executive leadership
  • Work w/ cross-functional stakeholders including engineers, TPMs, IT, operations and external customers, partners, and vendors.

Availability

• • This role will require extensive time in the datacenter (Santa Clara) and in HQ (Sunnyvale)

The Team

The Kernel team is responsible for the design, implementation, and performance tuning of deep learning operations on highly parallel custom processors. We are developing parallel and distributed algorithms to maximize hardware utilization and accelerate the training of deep neural networks to unprecedented speeds.

This involves:

• • Creating high-performance linear-algebra and machine-learning kernels for custom processors.
  • Designing and implementing parallel algorithms on a distributed hardware architecture.
  • Tuning and optimizing low-level assembly code within significant constraints of highly-optimized high performance hardware.
  • Understanding the tradeoffs of performance, compute, and memory and simultaneously optimize for all three.

The Role

As the Director of the Cerebras Kernel team, you will lead, build, and manage a team of highly talented and motivated software engineers in a fast-paced environment to solve toughest of the problems in rapidly evolving AI space.

Responsibilities

• Leading the team to develop a flexible and robust library of optimized kernels for primitive operations used by state-of-the-art neural network architectures
• Providing technical vision and guidance to team members in designing, analyzing, and optimizing algorithmic solutions
• Working with engineering leadership and product management teams to develop product roadmap
• Identifying hiring needs and filling them with top talent from industry and academia
• Mentoring and coaching team members considering both short-term execution and long-term career growth needs
• Identifying risks in product development schedule and take active measures to mitigate them
• Actively participating in defining next generation system architecture with hardware and systems teams and provide software perspective for feature prioritization
• Defining and enforcing best practices in software development process including coding style standards and peer reviews
• Identifying opportunities for deployment of tools and processes to improve engineering execution efficiency
• Driving sprint planning meetings

Skills & Qualifications

• Bachelor’s / Master’s degree or foreign equivalent in Computer Science, Engineering, or related field.
• 7+ years of related work experience in e.g. kernel design, implementation, and optimization, or high-performance parallel programming
• 5+ years of experience in building and managing engineering teams
• Familiarity with parallel algorithms and distributed memory systems
• Experience with assembly-level programming and optimization and strong knowledge of computer architecture fundamentals
• Programming fluency and extensive experience in C or C++ and Assembly languages
• Project and program management experience
• Familiarity with Agile development methodology
• Outstanding verbal and written communication skills
• Deep learning algorithms experience is a plus
• Experience working in a fast-paced, startup-like environment strongly preferred

About The Role

As a Kernel Engineer on our team, you will work with leaders from industry and academia at the intersection of hardware and software to develop state-of-the-art solutions for emerging problems in AI and HPC.

Our team of developers is responsible for the design, implementation, validation, and performance tuning of deep learning operations on highly parallel custom processors. We are developing a library of parallel and distributed algorithms to maximize hardware utilization and accelerate the training of deep neural networks to unprecedented speeds.

Responsibilities

• Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms
• Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system
• Using mathematical models and analysis to measure the software performance and inform design decisions
• Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries
• Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks
• Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems

Requirements

• Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields
• Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture
• Skilled in C++ and Python programming languages
• Good knowledge of library and/or API development best practices
• Strong debugging skills and knowledge of debugging complex software stack

Preferred Skills

• Experience in kernel development and/or testing
• Familiarity with parallel algorithms and distributed memory systems
• Experience in programming accelerators such as GPUs and FPGAs
• Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch
• Familiarity with HPC kernels and their optimization