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- Have significant software engineering experience
- Are results-oriented, with a bias towards flexibility and impact
- Pick up slack, even if it goes outside your job description
- Enjoy pair programming (we love to pair)
- Want to learn more about machine learning research
- Like working on systems and tools that make other people more productive
- Care about the societal impacts of your work
- High performance, large scale distributed systems
- Kubernetes
- Python
- Machine learning
- Implementing LLM finetuning algorithms, such as RLHF
- Profiling our reinforcement learning pipeline to find opportunities for improvement
- Building a system that regularly launches training jobs in a test environment so that we can quickly detect problems in the training pipeline
- Making changes to our finetuning systems so they work on new model architectures
- Building instrumentation to detect and eliminate Python GIL contention in our training code
- Diagnosing why training runs have started slowing down after some number of steps, and fixing it
- Implementing a stable, fast version of a new training algorithm proposed by a researcher
- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
- Comprehensive health, dental, and vision insurance for you and all your dependents.
- 401(k) plan with 4% matching.
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more
- Stipends for education, home office improvements, commuting, and wellness.
- Fertility benefits via Carrot.
- Daily lunches and snacks in our office.
- Relocation support for those moving to the Bay Area.
- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
- Private health, dental, and vision insurance for you and your dependents.
- Pension contribution (matching 4% of your salary).
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more
- Health cash plan.
- Life insurance and income protection.
- Daily lunches and snacks in our office.
- This compensation and benefits information is based on Anthropic's good faith estimate for this position as of the date of publication and may be modified in the future. Employees based outside of the UK or US will receive a different benefits package. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.
Machine Learning Systems Engineer - San Francisco, CA, United States - Anthropic
Description
About The Role
Our finetuning researchers train our production Claude models, and internal research models, using RLHF and other related methods. Your job will be to build, maintain, and improve the algorithms and systems that these researchers use to train models. You'll be responsible for improving the speed, reliability, and ease-of-use of these systems. 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. You may be a good fit if you: