Applied AI Engineer
On-siteNew York City, New York, United States or New York, United States
Job Summary
Develop, build, and apply modeling approaches—including adapting and post-training biological frontier models—for tasks in biological security and the design of precision biologics. Create evaluation frameworks to rigorously assess model performance, interrogate models to understand their biological learnings and limitations, and collaborate with computational biologists to curate datasets. Work with software engineers to scale model training infrastructure, visualize results for internal and external stakeholders, and represent the client to customers. Contribute to the client-wide research and development roadmap while staying current on state-of-the-art methods at the intersection of AI and biology.
Required Qualifications
- Experience with data-centric development and evaluation of ML models
- Highly proficient in Python and deep learning libraries (e.g., PyTorch)
- Experience with cloud computing platforms (e.g., AWS) and distributed systems
- Strong understanding of probability and statistics
Desired Qualifications
- Proven ability to design, implement, and evaluate new ideas in ML
- Experience with pre- or post-training language models, developing reasoning agents, and/or time series modeling
- Experience working with biological data or other types of noisy and heterogenous datasets
- Experience with ML-centric bioinformatics and structure-based tools (e.g., AlphaFold)
- Experience building data pipelining and training infrastructure
- Contributions to open-source projects
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