Anthropic
Research Engineer, Life Sciences
About this role
Anthropic seeks a Research Engineer to advance AI applications in life sciences, developing evaluation frameworks and training strategies that enhance model performance on complex biological tasks. You'll work across the full ML stack at the intersection of AI and biology, collaborating with world-class teams to build systems capable of supporting all phases of research and development.
What you'll do
- Develop novel evaluation frameworks to measure AI performance on life sciences tasks
- Design and implement training strategies that advance AI capabilities in biology
- Build and manage large-scale data pipelines for biological datasets
- Collaborate across research and engineering teams on AI systems for scientific discovery
- Work on model training and evaluation for language models applied to life sciences
- Navigate ambiguous research environments and develop solutions independently
What they're looking for
- Large language model training and evaluation
- Python programming
- ML development practices and tools
- Data pipeline engineering and management
- Scientific computing
- Reinforcement learning (preferred)
- Cloud deployment and containerization (Docker, Kubernetes)
- Cross-domain expertise (language modeling, systems engineering)
Benefits
- Annual salary: $350,000–$500,000 USD
- Hybrid work policy (minimum 25% in office)
- Visa sponsorship available
- Work on cutting-edge AI safety and beneficial AI systems
- Collaborative environment with world-class researchers
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Anthropic
Anthropic builds Claude, an AI assistant, and is hiring for engineering roles across infrastructure, data systems, and security that support both AI research operations and the company's internal technology needs. The company seeks infrastructure engineers, systems integrators, data scientists, and security specialists to build production-scale systems for training data pipelines, financial operations, developer productivity measurement, research infrastructure, and server firmware security.
- Website
- anthropic.com
Likely interview questions
- Walk us through your experience training and evaluating large language models. What specific challenges have you encountered and how did you address them?
- Describe a complex data pipeline you've built for large-scale datasets. What were the key design decisions and how did you handle data quality and validation?