About the job
This is a unique opportunity to join a small, high-impact team applying machine learning and bioinformatics to health initiatives. You will lead the architecture and implementation of the ML systems that take genomic, proteomic, and clinical signal from raw biology to actionable predictions — and you'll do it on a team where engineering decisions directly shape scientific outcomes.
Responsibilities
- Lead software architecture design for ML and bioinformatics systems that integrate genomic, proteomic, and clinical data.
- Develop high-performance APIs for model inference and pipeline orchestration across sequencing, multi-omics, and immunology workloads.
- Implement integration of ML models — including biological foundation models and structure-aware predictors — into prototype and production applications.
- Ensure efficient integration of selected models for tasks such as neoantigen prediction, MHC binding/presentation, and peptide ranking.
- Optimize system performance, scalability, and reliability for high-throughput bioinformatics pipelines and low-latency inference services.
Qualifications
Minimum
- 3+ years of non-internship professional software development experience
- 2+ years of non-intternship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
- Experience programming with at least one software programming language
Preferred
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent