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Research Engineer

Salary undisclosed

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Why Harvey

Harvey is transforming legal with LLM systems. We are backed by Sequoia ($21M Series A) and the OpenAI Startup Fund ($5M Seed) and have exceptional product-market fit.

  • Exceptional product market fit: multiple multi-million dollar deals with the largest professional service providers (e.g. PwC) and the largest law firms on Earth (e.g. Allen & Overy).
  • Massive demand: 15,000 law firms on our waitlist.
  • World-class team: ex-DeepMind, Google Brain, Meta AI, Tesla Autopilot. Former founding engineers at $1B+ startups like Superhuman and Glean.
  • Work directly with OpenAI to build the future of generative AI and redefine professional services.
  • Top of market cash and equity compensation.

Challenges

  • We are building systems that can automate the most complex knowledge work in the world, e.g. billion dollar litigations and corporate transactions.
  • Dealing with the most sensitive data in the world: client data from the largest companies in the world.
  • Working past the edge of published AI research: tackling problems far beyond the complexity of existing AI benchmarks.
  • Unsolved product, architectural, and business problems: natural language interfaces, prohibitively expensive evaluation of models, massive marginal costs, versioning / training / segregating models per task / legal system / practice area / client and client’s clients.

Role

You Will Develop And Improve Our AI Systems, Including

  • fine-tuning large language models,
  • developing model evals,
  • developing and implementing novel search and QA algorithms,
  • scraping and indexing niche legal datasets,
  • developing and evaluating large systems of interconnected LLMs,
  • dealing with hard engineering constraints like latency and expensive model inference, … and more.

Impact

  • Work directly with our founders, legal and research teams, and OpenAI.
  • Tackle unsolved research and engineering problems, including the hardest in the world relevant to LLMs in production.
  • Help build our applied research organization.

Qualifications

  • Evidence of exceptional ML engineering ability.
  • Publications in top AI conferences.
  • Experience at elite AI research labs (OpenAI, Google Brain, DeepMind).
  • Experience working in complex and high-stakes ML domains (self-driving cars, search, ads, quant finance).
  • Experience with LLMs or legal is not required.

Experience

  • 3-5+ years experience in ML engineering.