Member of Technical Staff - Research, Post-Training

Modal
New York, San Francisco
Workplace: OnsiteFull timeUSD 150,000 - 350,000 annuallyFunction: Education & TrainingSkills: ["Product sense","Shipping research","Ownership","Collaboration","Work in the open"]

Build and own end-to-end post-training research for the full LLM lifecycle platform, working with a research lead and Forward Deployed Engineers. Tackle high-impact bets across async and agentic RL, on-policy distillation, long-context RL, and small routing models, and collaborate with outside research labs. Partner with engineering to turn frontier techniques into products like post-training frameworks and distributed-training approaches, with results tied to production workloads.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Modal
Modal
2 months ago

Member of Technical Staff - Research, Post-Training

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 15 hours agoStatus: Live

Job Summary

Build and own end-to-end post-training research for the full LLM lifecycle platform, working with a research lead and Forward Deployed Engineers. Tackle high-impact bets across async and agentic RL, on-policy distillation, long-context RL, and small routing models, and collaborate with outside research labs. Partner with engineering to turn frontier techniques into products like post-training frameworks and distributed-training approaches, with results tied to production workloads.
Location: New York, San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Education & Training
Seniority: Mid level

Key Responsibilities

  • •Own end-to-end post-training research bets including async and agentic RL, on-policy distillation, long-context RL, and small routing models.
  • •Work directly with customers alongside Forward Deployed Engineers to train models and feed learnings back into research.
  • •Carry and expand collaborations with outside research labs, including work with ZLab on DFlash.
  • •Partner with engineering to turn frontier post-training techniques into products such as an opinionated post-training framework and distributed-training approaches.
  • •Help shape the research agenda by guiding future bets based on what works.

Pay and Benefits

Salary: USD 150,000 - 350,000 annually
Equity and Bonus:Equity

Key Requirements

  • •A research-leaning background in post-training LLMs, with work you can point to.
  • •Enough product sense to tell which frontier techniques matter to users and which stay academic.
  • •A record of shipping research that others can build on, in a lab or in industry.
  • •The drive to take a research bet from idea to result with minimal hand-holding and work openly with the team.
  • •Ability to work in-person, in the NYC or San Francisco office.
Experience:LLMsResearch labs
Skills:Product senseShipping researchOwnershipCollaborationWork in the open

Company Brief

Modal
Provides a serverless, high-performance cloud platform for AI, ML, and data workloads — offering instant autoscaling, elastic GPU access, and developer-first tooling to run inference, training, and batch jobs at scale.
Industry: Cloud Computing
Company Size: Small (11 to 50 employees)
Growth: Growth Stage Startup
Valuation: Unicorn (USD 1B+)
Funding: Series B
Headquarters: New York City, United States
Founded: 2021
WebsiteLinkedIn