Research Engineer/Research Scientist, Pre-training at Anthropic

Role overview

The Research Engineer/Research Scientist, Pre-training opening at Anthropic is centered on Deliver technical or research work for pre-training research for frontier AI models. The employer also lists Collaborate with research, engineering, security, product and business teams. and Improve reliability, testing, documentation and operational readiness. These responsibilities define the practical scope more clearly than the job title: applicants should be ready to explain what they have built, supported or delivered that relates directly to this work. The listing summary says: Anthropic is hiring a research engineer/research scientist, pre-training focused on pre-training research for frontier AI models. The named technologies include Python, Kubernetes, PyTorch.

The posting identifies Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field and Strong software engineering skills with a proven track record of building complex systems as relevant qualifications. Candidates should connect these requirements to evidence from their own work, including their individual contribution, technical decisions and outcomes. The listing describes the work arrangement as remote and gives the location as Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY / Boston, Massachusetts, United States / New York, New York, United States / San Francisco, California, United States / Seattle, Washington, United States. Confirm country eligibility, travel, employment terms and any details absent from this summary directly with Anthropic before applying. This overview is based on the employer-provided posting; it does not infer team structure or expectations that the source does not state.

Responsibilities

• Deliver technical or research work for pre-training research for frontier AI models.
• Collaborate with research, engineering, security, product and business teams.
• Improve reliability, testing, documentation and operational readiness.
• Translate complex technical questions into measurable systems or research outcomes.

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
• 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 you:
• Have significant software engineering experience
• Are results-oriented with a bias towards flexibility and impact

Technology in this role

• Python: The named technologies include Python, Kubernetes, .
• Kubernetes: The named technologies include Python, Kubernetes, .
• PyTorch: The named technologies include Python, Kubernetes, .
• large language models: We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language .

Role-specific candidate guide

Preparation notes based on the employer’s stated responsibilities and qualifications.

Understanding the scope. This Research Engineer/Research Scientist, Pre-training position at Anthropic is best assessed through the work described in the employer’s posting, rather than the title alone. The available role overview says: “The Research Engineer/Research Scientist, Pre-training opening at Anthropic is centered on Deliver technical or research work for pre-training research for frontier AI models. The employer also lists Collaborate with…” Read that statement together with the responsibilities below to understand the likely balance between delivery, coordination and technical decision-making. The role belongs to the technical area, but that label is only a guide to the work; the employer’s own requirements remain decisive. Before applying, check the original listing for reporting lines, product or team assignment, employment terms and any details that may have changed since this copy was checked. Where this page says a fact is not specified, treat it as an open question rather than an implied promise.

What the responsibilities signal. The posting specifically names “Deliver technical or research work for pre-training research for frontier AI models.”; “Collaborate with research, engineering, security, product and business teams.”; “Improve reliability, testing, documentation and operational readiness.”. For each duty, identify a project where you performed comparable work and be ready to describe the context, your own contribution, constraints, decisions, and measurable result. Explain how you moved.

Benefits

• Remote-friendly United States arrangement as stated; travel or office requirements vary by role.
• Opportunity to support Anthropic’s frontier AI and safety mission.

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.

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.

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