Member of Technical Staff, Research Engineer

About the role

As a Research Engineer, you'll bridge research and production. You'll turn validated methods, benchmarks, and evaluation infrastructure from our research team into dependable, production-grade features. You’ll be responsible for the entire lifecycle of an AI feature—from building the underlying systems to customizing the models that make them run. Your work will involve both robust system design and the pragmatic application of advanced machine learning techniques, including model fine-tuning when necessary. This role is for a product-minded research engineer who knows how to get the most out of modern AI and is obsessed with shipping reliable, high impact features.

We also publish our work on legal AI at intelligence.crosby.ai — take a look at the kinds of problems you'd be working on.

What you'll do

• Build core AI Systems: Design, build, and scale our primary AI features, including complex Retrieval Augmented Generation (RAG) pipelines and agentic workflows that make our models measurably better at contract review, playbook retrieval and docx editing.

• Build RL fine-tuning infrastructure: Stand up and harden RL training infrastructure (PPO, GRPO, and related methods) so researchers can train quickly and reliably at scale.

• Enable RL in a non-verifiable domain: Build reward pipelines, generators, and formal verification harnesses that make scalable RL possible in a domain like contract review.

• Customize Models for Impact: Selectively fine tune and adapt language models to improve their performance on highly specific legal tasks where off the shelf solutions fall short

• Ensure Production Quality: Develop evaluation and monitoring systems that catch regressions and reward hacking before they reach users.

• Apply AI Pragmatically: Stay on the frontier of AI research and identify the most effective techniques and tools to solve immediate product challenges.

• Collaborate to Ship: Work closely with product, backend, and our in house legal experts to deliver end to end solutions that make our users more effective.
  

Who you are

• Experience: 3+ years of professional software engineering experience building and shipping AI/ML-powered products, with deep proficiency in Python and a proven track record of scalable, production-grade systems.

• Post-training expertise: Familiarity with post-training techniques such as SFT and GRPO, plus hands-on experience with the systems and frameworks that run them at scale—distributed model training, VERL, and vLLM.

• Practical AI skills: Hands-on experience with LLM APIs (e.g., OpenAI, Anthropic), RAG, agentic workflows, and the full ML project lifecycle.

• Analytical and pragmatic: A data-driven approach to problem solving and strong intuition for when to build complex infrastructure versus ship a simple solution.

• Product-focused: Driven by user impact and skilled at making smart technical trade-offs to deliver value quickly.

• Ownership: You thrive on taking full responsibility for features, from initial concept through deployment and iteration.

Benefits & Perks

• Unlimited PTO

• Lunch & dinner in the office every day

• Dental insurance

• Vision insurance

• One Medical membership

• 401(k) match

• In-office desk setup stipend