Skills

Python Slack Monitoring Sales Research Training Machine Learning Programming Analytical Skills Large Language Models

Job Specifications

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.

About The Role

We are seeking an experienced Machine Learning Systems Engineer to join our Encodings and Tokenization team at Anthropic. This cross-functional role will be instrumental in developing and optimizing the encodings and tokenization systems used throughout our Finetuning workflows. As a bridge between our Pretraining and Finetuning teams, you'll build critical infrastructure that directly impacts how our models learn from and interpret data. Your work will be foundational to Anthropic's research progress, enabling more efficient and effective training of our AI systems while ensuring they remain reliable, interpretable, and steerable.

Responsibilities

Design, develop, and maintain tokenization systems used across Pretraining and Finetuning workflows
Optimize encoding techniques to improve model training efficiency and performance
Collaborate closely with research teams to understand their evolving needs around data representation
Build infrastructure that enables researchers to experiment with novel tokenization approaches
Implement systems for monitoring and debugging tokenization-related issues in the model training pipeline
Create robust testing frameworks to validate tokenization systems across diverse languages and data types
Identify and address bottlenecks in data processing pipelines related to tokenization
Document systems thoroughly and communicate technical decisions clearly to stakeholders across teams

You May Be a Good Fit If You

Have significant software engineering experience with demonstrated machine learning expertise
Are comfortable navigating ambiguity and developing solutions in rapidly evolving research environments
Can work independently while maintaining strong collaboration with cross-functional teams
Are results-oriented, with a bias towards flexibility and impact
Have experience with machine learning systems, data pipelines, or ML infrastructure
Are proficient in Python and familiar with modern ML development practices
Have strong analytical skills and can evaluate the impact of engineering changes on research outcomes
Pick up slack, even if it goes outside your job description
Enjoy pair programming (we love to pair!)
Care about the societal impacts of your work and are committed to developing AI responsibly

Strong Candidates May Also Have Experience With

Working with machine learning data processing pipelines
Building or optimizing data encodings for ML applications
Implementing or working with BPE, WordPiece, or other tokenization algorithms
Performance optimization of ML data processing systems
Multi-language tokenization challenges and solutions
Research environments where engineering directly enables scientific progress
Distributed systems and parallel computing for ML workflows
Large language models or other transformer-based architectures (not required)

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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

$320,000—$405,000 USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

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 part

About the Company

We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability. Know more