Research Engineer / Research Scientist, Tokens

Anthropic; San Francisco (CA); Hybrid; USD 350,000 - 500,000; Full time

Benefits offered by this job

Competitive compensation

Generous vacation

Parental leave

Flexible working hours

Office collaboration space

Job summary

Anthropic is looking for a Research Engineer to design and improve large-scale ML systems. This role involves enhancing infrastructure and running scientific experiments, requiring significant software engineering experience. Ideal candidates will have a Bachelor’s degree and relevant experience. The annual salary ranges from $350,000 to $500,000 USD. Benefits include flexible working hours and competitive compensation. The position is based in San Francisco, requiring hybrid work attendance.

Qualifications

• Significant software engineering experience.
• Minimum education of Bachelor's degree or equivalent.
• Experience relevant to the role through coursework or training.

Responsibilities

• Build large scale ML systems from the ground up.
• Make the cluster more reliable for big jobs.
• Run and design scientific experiments.
• Improve dev tooling.

Skills

Software engineering experience

Results-oriented mindset

Flexibility

Pair programming

Interest in machine learning research

Concern for societal impacts

Education

Bachelor’s degree or equivalent

Tools

GPUs

Kubernetes

Pytorch

OS internals

Language modeling with transformers

Reinforcement learning

Large-scale ETL

Job description

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 want to build large scale ML systems from the ground up. You care about making safe, steerable, trustworthy systems. As a Research Engineer, you'll touch all parts of our code and infrastructure, whether that includes making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling. You're excited to write code when you understand the research context and the broader importance.

You May Be a Good Fit If You

• 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
• Care about the societal impacts of your work

Strong Candidates May Also Have Experience With

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL

Representative Projects

• Optimizing the throughput of a new attention mechanism
• Comparing the compute efficiency of two Transformer variants
• Making a Wikipedia dataset in a format models can easily consume
• Scaling a distributed training job to thousands of GPUs
• Writing a design doc for fault tolerance strategies
• Creating an interactive visualization of attention between tokens in a language model

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 sponsor visas.

Benefits

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.