Research Engineer, Production Model Post-Training
- Pay
- $350,000 – $500,000 per year
- Location
- San Francisco, CA · Hybrid
- Job type
- Full-time
- Level
- Lead / Staff
- Education
- Bachelor's degree
- Listed
- 13 days ago
Skills & highlights for this role
- Python
- Deep learning frameworks
- Distributed computing
- Strong software engineering
- Experience building complex ML systems
- Experience training, fine-tuning, or evaluating large language models
Also useful
- Experience with LLMs
- Interest in AI safety and responsible deployment
- Hands-on experience with frontier AI systems
About the role
Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.
You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies. Your work will directly impact the quality, safety, and capabilities of our production models.
Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends.
Responsibilities
- Implement and optimize post-training techniques at scale on frontier models
- Conduct research to develop and optimize post-training recipes that directly improve production model quality
- Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation
- Develop tools to measure and improve model performance across various dimensions
- Collaborate with research teams to translate emerging techniques into production-ready implementations
- Debug complex issues in training pipelines and model behavior
- Help establish best practices for reliable, reproducible model post-training
You may be a good fit if you
- Thrive in controlled chaos and are energised, rather than overwhelmed, when juggling multiple urgent priorities
- Adapt quickly to changing priorities
- Maintain clarity when debugging complex, time-sensitive issues
- Have strong software engineering skills with experience building complex ML systems
- Are comfortable working with large-scale distributed systems and high-performance computing
- Have experience with training, fine-tuning, or evaluating large language models
- Can balance research exploration with engineering rigor and operational reliability
- Are adept at analyzing and debugging model training processes
- Enjoy collaborating across research and engineering disciplines
- Can navigate ambiguity and make progress in fast-moving research environments
- Strong candidates may also: Have experience with LLMs
- Have a keen interest in AI safety and responsible deployment
- We welcome candidates at various experience levels, with a preference for senior engineers who have hands-on experience with frontier AI systems. However, proficiency in Python, deep learning frameworks, and distributed computing is required for this role.
Pay and benefits
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary
$350,000
- $500,000
USD
Logistics
Minimum education
Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study
A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience
Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy
Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship
- We do sponsor visas!
- However, we aren't able to successfully sponsor visas for every role and every candidate.
- But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification.
Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
- To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses.
- In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic.
- Be cautious of emails from other domains.
- Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day.
- If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
- We believe that the highest-impact AI research will be big science.
- At Anthropic we work as a single cohesive team on just a few large-scale research efforts.
- And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles.
- We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science.
- We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.
- As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Pay and benefits
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
From Anthropic's careers page, first listed on Rolev.ai on October 27, 2026. Rolev.ai is not the employer.
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Common questions
What is the salary for the Research Engineer, Production Model Post-Training role at Anthropic?
The Research Engineer, Production Model Post-Training posting at Anthropic states compensation of $350,000 – $500,000 per year. It is listed as a full-time position. Final pay may depend on location, experience, and interview evaluation on Anthropic's official career site.
Where is the Research Engineer, Production Model Post-Training job at Anthropic located?
This Research Engineer, Production Model Post-Training position at Anthropic is located in San Francisco, CA (Hybrid). Always check Anthropic's application page for specific state eligibility or relocation policies.
What qualifications are required for Research Engineer, Production Model Post-Training at Anthropic?
For the Research Engineer, Production Model Post-Training role, Anthropic highlights a bachelor's degree; experience with Python, Deep learning frameworks, Distributed computing, Strong software engineering, Experience building complex ML systems, Experience training, fine-tuning, or evaluating large language models. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Research Engineer, Production Model Post-Training position at Anthropic?
This listing links directly to Anthropic's application page. You can apply directly on Anthropic's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.