Post-Training Applied Researcher
Company websitebaseten.co (Baseten, opens in new tab)
Base salary $200K to $275K
Employer-published annual base salary, USD. Advertised base range in San Francisco, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSan Francisco, CA
- WorkplaceHybrid
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
This role sits at the applied end of our post-training research efforts. You will work directly with stakeholders from the world’s fastest-growing AI companies to post-train open-source models that outperform frontier closed models on their specialised tasks. Your day-to-day is finding creative ways to extract signal from complex, domain-specific datasets and building the reward functions, environments, eval harnesses, and training pipelines that turn that signal into better models. The models you train ship to production and reach millions of users.
We are looking for people with hands-on LLM fine-tuning and RL experience. Researchers who are excited by the prospect of shipping models into production, who can translate a customer's domain-specific requirements into an effective training curriculum, and who know when to be rigorous and when to iterate fast.
RECENT RESEARCH
Dense, on-policy or both?
Repeated kv cache for long-running agents
Distillation without the dark – replicating black-box on-policy distillation on Baseten
RESPONSIBILITIES
Design and run post-training pipelines: SFT, GRPO, DPO, RLVR, reward function engineering, and synthetic data generation.
Build task-specific training environments and evals tailored to customer domains like healthcare, code generation, and legal, spanning multi-turn tool use, sandboxed execution, and agentic workflows.
Work directly with customers to translate production data into training signal, designing reward loops from real usage patterns and handling distribution shift.
Run and analyze training experiments end-to-end: diagnose reward hacking, importance sampling drift, and advantage estimation instabilities.
Publish findings at top venues and contribute to Baseten's open-source training libraries.
QUALIFICATIONS
Hands-on experience training LLMs with reinforcement learning — demonstrated understanding of GRPO or PPO beyond recipe-level reproduction, including group advantage computation, clipped objectives, and KL penalty design
Strong intuition for reward engineering: the ability to distinguish between a reward that trains effectively and one that will exploit at scale
Experience building multi-turn agent environments with tool use, not limited to single-turn question-answering setups
Comfort working across the full pipeline from dataset construction through training, evaluation, and deployment
Experience with production ML systems. Preference for candidates who have closed a training–inference loop where production data feeds back into model improvement
PREFERRED QUALIFICATIONS
Experience with RL training frameworks
Publications at NeurIPS, ICML, ICLR, focused on RL for LLMs, reward modeling, or alignment
BENEFITS
Competitive compensation, including meaningful equity
(U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
Paid parental leave
Fertility and family-building stipend through Carrot
(U.S. only) Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Source: Baseten on Ashby · View original posting (opens in new tab)
This listingPost-Training Applied Researcher$200K to $275K
Marketing Analytics Manager$200K to $240K
Forward Deployed Engineer (Training)$200K to $400K
Sales Development Manager$200K to $240K
Post-Training Research Engineer$200K to $275K
Product Marketing Manager, Solutions$190K to $220K
Post-Training Research Scientist$210K to $285K
Chart as a table
| Role | Published base |
|---|---|
| Post-Training Applied Researcher (this listing) | $200K - $275K |
| Marketing Analytics Manager | $200K - $240K |
| Forward Deployed Engineer (Training) | $200K - $400K |
| Sales Development Manager | $200K - $240K |
| Post-Training Research Engineer | $200K - $275K |
| Product Marketing Manager, Solutions | $190K - $220K |
| Post-Training Research Scientist | $210K - $285K |
Observed changes
- Began meeting the published-salary criteria
- First observed on the employer's board
- Observed since
- Employer-stated posting date
- 2026-10-07
Where this pay comes from
Location as the employer wrote it: San Francisco
USD 200,000 – 275,000 · 1 YEAR · Salary
- Method
- Structured pay field published by the employer
- Checked
- Rule set
- us-base-v2
The employer's job board publishes this pay as a dedicated data field. We read the field directly; no interpretation was needed.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
