Research Engineer / Scientist, Pre-training

Anthropic

New York (NY)

Hybrid

USD 500,000 - 850,000

Full time

12 hours ago
Be an early applicant

Get a reply from this employer

Your resume and cover letter, tailored to exactly what they’re hiring for.

Get past ATS filters

Job summary

Anthropic is seeking a Research Engineer to join our Pre-training team, developing the next generation of large language models at scale. You will bridge research ideas and engineering, designing experiments and building reliable training pipelines. Ideal candidates hold an advanced degree, excel in Python and PyTorch, and can balance rigorous research with pragmatic engineering.

You will collaborate across disciplines to advance steerable, safe AI. Location is flexible within the U.S.

Qualifications

  • Advanced degree required (MS or PhD) in Computer Science, ML, or related field.
  • Strong software engineering background with experience building complex systems.
  • Expertise in Python and deep learning frameworks, preferably PyTorch.
  • Experience with large-scale ML, language models, and systems.
  • Ability to balance research goals with engineering constraints.
  • Strong problem-solving and communication skills.

Responsibilities

  • Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development.
  • Independently lead small research projects and collaborate on larger initiatives.
  • Design, run, and analyze experiments related to large language models.
  • Optimize and scale training infrastructure for efficiency and reliability.
  • Develop and improve dev tooling to boost team productivity.
  • Contribute to the full stack from low-level optimizations to high-level model design.

Skills

Software engineering
Python
Deep learning
Communication
Collaborative work
Research-minded

Education

Advanced degree (MS/PhD) in CS/ML

Tools

PyTorch
Kubernetes
GPUs
OS internals

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.

About The Role

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre‑training 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 optimizations 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 modeling using transformer architectures
  • Knowledge of reinforcement learning techniques
  • Background in large‑scale ETL processes
You’ll thrive in this role if
  • 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, understand and interpret deep neural networks, or develop new models to support these areas of research
  • View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights
  • Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long‑term.
Sample Projects
  • Optimizing the throughput of novel attention mechanisms
  • Comparing compute efficiency of different Transformer variants
  • Preparing large‑scale datasets for efficient model consumption
  • Scaling distributed training jobs to thousands of GPUs
  • Designing fault tolerance strategies for our training infrastructure
  • Creating interactive visualizations of model internals, such as attention patterns
Annual Salary

$500,000—$850,000 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 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.
How We’re Different

We believe that the highest‑impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large‑scale research efforts. And we value impact — advancing our long‑term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest‑impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT‑3, Circuit‑Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. 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. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Get your free, confidential resume review.

or drag and drop your file here.

Similar jobs

Similar jobs worth comparing

Research Engineer / Scientist, Pre-training
Research Engineer / Scientist, Pre-training

Anthropic • San Francisco (CA)

On-site
USD 500,000 - 850,000
Research Engineer / Scientist, Pre-training
Research Engineer / Scientist, Pre-training

Anthropic • Seattle (WA)

Hybrid
USD 500,000 - 850,000
Research Engineer/Research Scientist, Pre-training
Research Engineer/Research Scientist, Pre-training

Anthropic • San Francisco (CA)

Hybrid
USD 340,000 - 425,000
Competitive compensation and benefits
Generous vacation and parental leave
Flexible working hours
Research Engineer / Scientist, Pre-training
Research Engineer / Scientist, Pre-training

Anthropic • United States

Remote
USD 500,000 - 850,000
Remote role
Flexible hours
Visa sponsorship available
Research Engineer, Discovery
Research Engineer, Discovery

Anthropic • San Francisco (CA)

Hybrid
USD 350,000 - 850,000
Equity donation matching
Vacation and parental leave
Flexible working hours
+1
Pre-training Data Infrastructure Engineer
Pre-training Data Infrastructure Engineer

Anthropic • San Francisco (CA)

Hybrid
USD 500,000 - 850,000
Equity donation matching
Generous vacation and parental leave
Flexible working hours
+1
Research Engineer / Research Scientist, RL Frontiers
Research Engineer / Research Scientist, RL Frontiers

Anthropic • Seattle (WA)

Hybrid
USD 500,000 - 850,000
Staff Research Engineer – AI Discovery Scientist
Staff Research Engineer – AI Discovery Scientist

Anthropic • San Francisco (CA)

Hybrid
USD 315,000 - 560,000
Competitive compensation and benefits
Flexible working hours
Generous vacation and parental leave
Staff Research Engineer, Discovery Team
Staff Research Engineer, Discovery Team

Anthropic • New York (NY)

Hybrid
USD 350,000 - 850,000
Equity donation matching
Generous vacation
Parental leave
+2
Research Engineer / Research Scientist, RL Frontiers
Research Engineer / Research Scientist, RL Frontiers

Anthropic • New York (NY)

On-site
USD 500,000 - 850,000