Research Engineer, Life Sciences
Research Engineer developing novel evaluation frameworks and training strategies for AI systems in life sciences and biology. Requires experience training/evaluating LLMs, Python/ML proficiency, and data pipeline expertise; biology background preferred but not required.
About the job
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
Education
- 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
Compensation
Annual Salary: $350,000—$500,000 USD
Skills
LLMs, Python, Machine Learning, Data Pipelines, Reinforcement Learning, Pretraining, Docker, Kubernetes, Biological Datasets, Scientific Computing
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