Join Anthropic as a Research Engineer to advance AI in life sciences through innovative machine learning techniques.
Posted by employer 3 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 2 hours ago
Skills & Technologies
Requirements
- Experience
- 8+ years
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Benefits
Joblaze summary
In the role of Research Engineer on the Life Sciences team at Anthropic, the individual will focus on developing innovative evaluation frameworks and training strategies to enhance AI applications in biology. Key skills include expertise in machine learning, proficiency in Python, and experience with large datasets and model training. This position is ideal for seasoned professionals with a strong background in AI and a collaborative mindset, though prior life sciences experience is not mandatory. Anthropic emphasizes a cohesive team approach to tackle significant research challenges in AI.
Joblaze insights
- Listed about 3 months ago — first seen on Joblaze July 4, 2026. Last confirmed on Anthropic's careers page October 10, 2026.
- Salary band is above the typical range for AI/ML roles (median ~$190,000).
- Starts above 96% of 206 comparable senior ai/ml roles in United States that list Python we track (median $181,000 across 70 companies). See Python salary trends
- Python appears in 52.8% of 551 comparable senior ai/ml roles in United States; Docker appears in 4.7% of 551 comparable senior ai/ml roles in United States.
Quick facts
- Is the Research Engineer, Life Sciences role remote?
- It's hybrid — Anthropic expects some on-site time in San Francisco, CA.
- What's the salary range?
- Anthropic lists $350,000–$500,000 for this role.
- How much experience is required?
- At least 8 years of relevant experience for this Research Engineer, Life Sciences role.
- Where is the role based?
- Anthropic is hiring for this position in San Francisco, CA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Docker, Kubernetes, Machine Learning, Python, reinforcement learning.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Research Engineer, Life Sciences role at Anthropic.
From the original posting
About Anthropic
About the Role
We're seeking an exceptional Research Engineer to join our Life Sciences team at Anthropic. Our team is organized around the north star goal of accelerating progress in the life sciences, from early discovery through translation, by an order of magnitude. Our team likes to think across the whole model stack. In this role, you'll combine your deep expertise in machine learning engineering to develop novel evaluation frameworks and training strategies that push the frontier of what AI can achieve in biology.
You'll work at the intersection of cutting-edge AI and the biological sciences, developing rigorous methods to measure and improve model performance on complex scientific tasks. You'll collaborate closely with world-class researchers and engineers to build AI systems that can engage in all phases of research and development, while maintaining our commitment to safety and beneficial impact.
Previous experience in life sciences is welcome, but not required for this role.
Minimum Qualifications
- Demonstrated experience training and evaluating large language models
- Proficiency in Python and familiarity with modern ML development practices
- Experience building and managing data pipelines for large-scale datasets
- Comfortable navigating ambiguity and developing solutions in rapidly evolving research environments
- Strong written and verbal communication skills, with the ability to work independently while collaborating effectively across cross-functional teams
Preferred Qualifications
- 8+ years of machine learning experience
- Prior work experience in AI and biology, including graduate studies (molecular biology, biochemistry, computational biology, or related fields)
- Experience working with large-scale biological datasets
- Published research or practical experience in scientific AI applications or long-horizon reasoning
- Background in reinforcement learning and/or pretraining
- Knowledge of containerization technologies (e.g., Docker, Kubernetes) and cloud deployment at scale
- Demonstrated ability to work across multiple domains, such as language modeling, systems engineering, and scientific computing
- Contributions to open-source scientific software or databases
The annual compensation range for this role is listed below.
Logistics
Standard company text repeated across Anthropic's postings is omitted here.