RL Systems Engineer: Build Safe, Steerable AI

Anthropic; New York (NY); Hybrid; USD 500,000 - 850,000; Full time

Benefits offered by this job

Equity donation matching

Generous vacation

Parental leave

Flexible working hours

Office space in SF

Job summary

Anthropic is seeking an ML Systems Engineer to join the Reinforcement Learning Engineering team. You will build, maintain, and improve algorithms and systems used to train models, focusing on speed, reliability and usability to empower researchers working on Claude and related models.

You have 4+ years of software engineering experience, enjoy working on scalable systems, and are motivated by producing impactful results in ML research with a bias toward collaboration and flexibility.

Qualifications

• Bachelor’s degree or equivalent in a relevant field.
• 4+ years of software engineering experience.
• Location-based hybrid policy: staff are in offices at least 25% of the time; visa sponsorship available.

Responsibilities

• Build, maintain and improve RL training systems and infrastructure used by researchers.
• Improve speed, reliability and usability of reinforcement learning pipelines.
• Support and empower research teams to train models and iterate on finetuning methods (e.g., RLHF).

Skills

Software engineering

Distributed systems

Machine learning

Python

Collaboration

Education

Bachelor’s degree or equivalent

Tools

Python

Job description

Anthropic is seeking an ML Systems Engineer to join the Reinforcement Learning Engineering team. You will build, maintain, and improve algorithms and systems used to train models, focusing on speed, reliability and usability to empower researchers working on Claude and related models.

You have 4+ years of software engineering experience, enjoy working on scalable systems, and are motivated by producing impactful results in ML research with a bias toward collaboration and flexibility.