Research Engineer, Production Model Post-Training
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA · AI Research & Engineering · listed April 1, 2025
The shape of it
Seniority
Not stated
Where
Hybrid
Stated pay
$350,000 – $500,000 USD
Requirements listed
10
Length
971 words
In the posting’s own words
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.
What it asks for · 10
- 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
Also a plus
- Have experience with LLMs
- Have a keen interest in AI safety and responsible deployment
What the job covers
- 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
Tools and skills named
Models & research
- Fine-tuning2×
- LLM2×
- Deep learning
- Machine learning
- Reinforcement learning
Languages
- Python2×
Cloud & infra
- Distributed systems
Words the posting leans on
- model12×
- post-training7×
- research7×
- experience5×
- production5×
- engineering4×
- complex3×
- safety3×
- systems3×
- training3×
- alignment2×
- capabilities2×
- computing2×
- conduct2×
- debugging2×
- develop2×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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