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Member of Technical Staff, Machine Learning
Engineering
on site: New York City
added Tue Oct 24, 2023
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About the role

Our technology powers financial services firms who are running due diligence on billion-dollar deals and want to make their analysts faster and smarter.

You will own the full ML pipeline from project ideation, data curation, project execution, and continuous evaluation in production. You'll have close feedback loops with users and our Product team. In the past few months, we have:

  • Built sub-second, layout-aware semantic search on top of data in any format
  • Developed automatic safeguards to control generative models
  • Fine-tuned foundation models to scale beyond narrow academic benchmarks
  • Leveraged state-of-the-art NLP models to turn semi-structured data into actionable customer insights
  • Developed regression tests to enable rapid experimentation

This role is based out of our New York City office in Soho.

Responsibilities

  1. Close the publication-to-practice gap: Turn proof-of-concept papers into a real customer feature the week they’re published
  2. Own product features: Solve a customer need end-to-end in a way they can actually understand and trust
  3. Know the user: Understand real use cases and pain points deeply

Who You Are

  1. 5+ years ML research or ML engineering at a venture-backed startup or top industry AI group
  2. Embraces rapid prototyping with an emphasis on user feedback
  3. Autonomous and excited about taking ownership over major initiatives
  4. Extreme passion for learning, growth, and leadership
  5. Focused on real user impact instead of academic work

Compensation and Benefits

The annual salary/OTE range for 5+ years of experience for this role is $150,000 – $225,000 with target equity + benefits

Benefits:

  • Medical, dental, and vision insurance coverage for you
  • 401K
  • Two weeks PTO
  • Free meals

Hebbia is reinventing the search engine to intelligently answer the world's most complex questions. Our AI understands and reasons over written knowledge to synthesize meaningful responses for users in seconds. We've raised significant funding from Peter Thiel, Index Ventures (via Mike Volpi), Jerry Yang (founder of Yahoo), Ram Sriram (one of the first investors in Google), and others, and have built the fastest-moving team in the world.