Apply to Helm.aiYou will:
- Work with the Platform team to build highly impactful development tools and systems for all engineers at the company.
- Improve engineering and research productivity by creating efficient systems for building, testing, and deploying code and ML pipelines (CI/CD and MLOps).
- Optimize the runtime environment for ML training in the cloud and real-time processing of vehicle data on the road.
- Ensure that our ML models and SDK are thoroughly tested and can be shipped to customers in a reliable, reproducible, and scalable way.
You have:
- A proven track record of working with at least one backend programming language, e.g. C++, Java, Python, Go, etc.
- Worked with modern CI/CD and build systems, e.g. Bazel, Docker, GitHub Actions, etc.
- The ability to work in a fast-paced environment to deliver customer projects.
- An attention for detail and desire to take initiative in ambiguous situations.
- A desire to be a champion for maintaining healthy code and best practices.
We offer:
- Competitive health insurance options
- 401K plan management
- Remote-friendly and flexible team culture
- Free lunch and fully-stocked kitchen in our South Bay office
- Additional perks: monthly wellness stipend, office set up allowance, company retreats, and more to come as we scale
- The opportunity to work on one of the most interesting, impactful problems of the decade
Helm.ai is proud to be an equal opportunity employer building a diverse and inclusive workforce. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Helm.ai are considered the property of Helm.ai and are not subject to payment of agency fees.
Helm.ai builds AI software for autonomous driving and robotics. Our "Deep Teaching" methodology is uniquely data and capital efficient, allowing us to surpass traditional approaches. Our unsupervised learning software can train neural networks without the need for human annotation or simulation and is hardware-agnostic. We work with some of the world's largest automotive manufacturers and we've raised over $70M from Honda, Goodyear Ventures, Mando, and others to help us scale.
Our team is made up of people with a diverse set of experiences in software and academia. We work together towards one common goal: to integrate the software you'll help us build into hundreds of millions of vehicles.