Research Systems Engineer
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Before you apply
Salary$190k – $310k
LocationSan Francisco
Work modeon-site
Typefull-time
SenioritySenior
DepartmentResearch Systems
EquityIncluded
Company size51–200 people
PostedMar 10, 2026 · 8mo ago
Verified live2d ago
May no longer be actively hiring
Posted by the company on Mar 10, 202671% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
Experience training or serving large language models
Experience building RL environments and evaluations for language models
Proficiency in PyTorch, JAX, or similar ML frameworks, with experience in distributed training
Strong experimental design skills — you know how to set up experiments that actually answer questions
Background in pre-training or post-training research
Previous experience in high-performance computing environments or large-scale clusters
Contributions to open-source ML research or infrastructure
Demonstrated technical creativity through published research, OSS contributions, or side projects
Skills
PyTorch
JAX
distributed training
Benefits
Health insurance
Unlimited PTO
Parental leave
Meals
Transportation
Relocation
401(k)
The role
As a research systems engineer, you’ll train frontier-scale models and develop the methods that make continual learning work inside enterprise environments. You’ll design and run experiments at scale, explore cutting-edge RL techniques, and build the tools that let us understand what’s actually happening during training. This role sits at the intersection of research and systems. You’ll invent new algorithms alongside researchers, then work with infrastructure engineers to run them on GPUs.
What you’ll do
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Post-train frontier-scale language models on enterprise tasks and environments
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Explore and develop RL techniques, co-designing algorithms and systems
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Contribute to Alchemy, our data research program for generating signal-rich training environments from production data
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Build high-performance internal tools for probing, debugging, and analyzing training runs
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Partner with infrastructure engineers to scale training and inference efficiently
What we’re looking for
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Experience training or serving large language models
•
Experience building RL environments and evaluations for language models
•
Proficiency in PyTorch, JAX, or similar ML frameworks, with experience in distributed training
•
Strong experimental design skills — you know how to set up experiments that actually answer questions
Strong candidates also have
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Background in pre-training or post-training research
•
Previous experience in high-performance computing environments or large-scale clusters
•
Contributions to open-source ML research or infrastructure
•
Demonstrated technical creativity through published research, OSS contributions, or side projects
Benefits
The U.S. base salary range for this full-time position is $190,000–$310,000. Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a comprehensive benefits package designed to support you both personally and professionally. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
Benefits & Logistics
This role is based in San Francisco. We work from our office in the Mission. We offer:
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Competitive compensation and equity
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100% employer-paid health insurance coverage for you and your family
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Unlimited PTO
•
Paid parental leave
•
Daily lunches and dinners
•
Transportation and relocation support
•
5% 401(k) match
Legal
We sponsor visas. While we can’t guarantee success for every candidate or role, if you’re the right fit, we’re committed to working through the process with you. We encourage you to apply even if you do not believe you meet every single qualification. As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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