Research Engineer, Pre-training
Join Anthropic, a public benefit corporation dedicated to building safe, interpretable, and steerable AI systems.
About the role
We are seeking a Research Engineer to join our Pretraining team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting‑edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.
Key Responsibilities
* Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development.
* Independently lead small research projects while collaborating with team members on larger initiatives.
* Design, run, and analyze scientific experiments to advance our understanding of large language models.
* Optimize and scale our training infrastructure to improve efficiency and reliability.
* Develop and improve dev tooling to enhance team productivity.
* Contribute to the entire stack, from low‑level optimisations to high‑level model design.
Qualifications
* Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field.
* Strong software engineering skills with a proven track record of building complex systems.
* Expertise in Python and experience with deep learning frameworks (PyTorch preferred).
* Familiarity with large‑scale machine learning, particularly in the context of language models.
* Ability to balance research goals with practical engineering constraints.
* Strong problem‑solving skills and a results‑oriented mindset.
* Excellent communication skills and ability to work in a collaborative environment.
* Care about the societal impacts of your work.
Preferred Experience
* Work on high‑performance, large‑scale ML systems.
* Familiarity with GPUs, Kubernetes, and OS internals.
* Experience with language modelling using transformer architectures.
* Knowledge of reinforcement learning techniques.
* Background in large‑scale ETL processes.
You’ll Thrive In This Role If You
* Have significant software engineering experience.
* Are results‑oriented with a bias towards flexibility and impact.
* Willingly take on tasks outside your job description to support the team.
* Enjoy pair programming and collaborative work.
* Are eager to learn more about machine learning research.
* Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large‑scale AI research projects.
* Are working to align state‑of‑the‑art models with human values and preferences.
* View research and engineering as two sides of the same coin and seek to understand all aspects of our research program to maximise your impact.
* Have ambitious goals for AI safety and general progress.
Sample Projects
* Optimise the throughput of novel attention mechanisms.
* Compare compute efficiency of different Transformer variants.
* Prepare large‑scale datasets for efficient model consumption.
* Scale distributed training jobs to thousands of GPUs.
* Design fault tolerance strategies for our training infrastructure.
* Create interactive visualisations of model internals, such as attention patterns.
Diversity & Inclusion
At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.
Compensation
Annual Salary: £250,000‑£270,000 GBP + equity, benefits, and potential incentive compensation.
Logistics
Education requirements: At least a Bachelor's degree in a related field or equivalent experience.
Location‑based hybrid policy: Staff are expected to be in one of our offices at least 25% of the time. Some roles may require a higher percentage.
Visa Sponsorship
We sponsor visas when possible, but we may not be able to sponsor every candidate. We will make every reasonable effort to obtain a visa if you receive an offer.
We Encourage You to Apply
We encourage you to apply even if you do not meet every single qualification. Not all strong candidates will meet every qualification, and we believe diverse perspectives are essential.
How We’re Different
We believe that the highest‑impact AI research requires big science. Our team works collectively on a few large‑scale projects, prioritising steerable, trustworthy AI over smaller puzzles.
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