FewerJobs.
All jobs

Research Engineer, Frontier Capabilities

Lila Sciences - Cambridge, MA USA; San Francisco, CA USA

Posted Oct 6, 2025

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
Not verified
Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
Not verified
Verification
Not verified
Salary
Not verified not verified - source not recorded; timestamp not recorded
401(k) match
Not verified

Was this benefit information wrong? Tell us.

Schedule

Shift type
Not verified
Weekend work
Not verified

Application

Cover letter
Not verified
Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Research Engineer, Frontier Capabilities Cambridge, MA USA; San Francisco, CA USA Your Impact at LILA The AI Research team is tackling one of the most exciting, open problems in AI: training LLMs to run long-horizon scientific discovery tasks. Our approach spans the full post-training stack - from SFT to asynchronous RL on agentic harnesses - teaching models to plan, use tools, and learn from experience in domains where the ground truth isn't a preference label, but a scientific result. We're rapidly growing our Research Engineering org and seeking talented engineers and ML practitioners across levels to design, build, and optimize systems to push this frontier: scaling post-training, sharpening reasoning, and unlocking compute-intensive agentic-harness training. This is a rare chance to join an early team with the autonomy, flexibility, and compute to tackle frontier science problems. We operate with high agency, and a bias toward execution. Below are several focus areas within the team. We ask that candidates select the stream that best matches their experience and excitement. Work Streams Stream A: GPU Optimization & Training Performance Maximize hardware utilization across 100B+ parameter asynchronous RL training runs. Responsibilities include profiling, performance optimization, custom kernel development, communication-computation overlap, and long-context throughput improvements. You set and maintain the performance baseline. Stream B: Stack & Infrastructure Own the post-training infrastructure end-to-end - supervised fine-tuning, asynchronous RL with tool integration, and data pipelines. Build modular, reproducible workflows with single-command execution. Manage upstream framework upgrades and deliver composable pipelines spanning Data, SFT, and RL stages. You

Read the full description at job-boards.greenhouse.io. FewerJobs shows a source-linked preview and links to the original posting.

Apply at job-boards.greenhouse.io

Apply link not verified; last-live date unavailable.

What verified means

Verified means a displayed claim has a recorded source field, a source URL when available, and a timestamp showing when FewerJobs checked or enriched the evidence.

Related jobs