Iambic Therapeutics, Inc - Software Engineer I/II, Machine Learning
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Requirements
• Engineer I: Minimum of 5 years of related experience with a Bachelor’s degree in a scientific field; or 3 years and a Master’s degree; or equivalent work experience. • Engineer II: 8+ years relevant experience with a bachelor’s degree in a scientific field; or PhD with 3+ years; or equivalent experience. • Strong modern Python development (packaging, type hints, testing, performance), with experience in building production services and libraries. • Hands-on with ML model lifecycle and tooling (e.g. PyTorch, Hugging Face, vLLM/Triton/ONNX Runtime); data tooling (e.g. Pandas, Arrow, S3, Parquet); and workflow orchestration (e.g. Prefect, Airflow, Luigi). • Cloud deployment experience (AWS preferred), including containerization, IaC patterns, and GPU workload considerations. • Experience in scientific domains or drug discovery is a plus; ability to collaborate with scientists and communicate across disciplines is essential.
Responsibilities
• Design, implement, and maintain production-grade ML workflows (fine-tuning, batch/online inference, evaluation) with strong observability and CI/CD. • Deploy GPU-accelerated ML services and jobs using modern tooling and cloud-based orchestration. • Collaborate with ML scientists and cross-functional teams to capture requirements, scope milestones, and deliver features into user workflows and services. • Conduct code reviews and mentor peers on software engineering and MLOps best practices. • Engineer I: Minimum of 5 years of related experience with a Bachelor’s degree in a scientific field; or 3 years and a Master’s degree; or equivalent work experience. • Engineer II: 8+ years relevant experience with a bachelor’s degree in a scientific field; or PhD with 3+ years; or equivalent experience. • Strong modern Python development (packaging, type hints, testing, performance), with experience in building production services and libraries. • Hands-on with ML model lifecycle and tooling (e.g. PyTorch, Hugging Face, vLLM/Triton/ONNX Runtime); data tooling (e.g. Pandas, Arrow, S3, Parquet); and workflow orchestration (e.g. Prefect, Airflow, Luigi). • Cloud deployment experience (AWS preferred), including containerization, IaC patterns, and GPU workload considerations. • Experience in scientific domains or drug discovery is a plus; ability to collaborate with scientists and communicate across disciplines is essential. • Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai. • MISSION & CORE VALUES • Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.
Benefits
• Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • LinkedIn Job Listing • A different job posting site • Describe one ML system you personally built and deployed to production. Include the tools used (e.g., PyTorch, AWS, orchestration), how it was deployed (batch or real-time), and one specific issue you encountered in production and how you resolved it. Be Specific
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