Software Engineer I/II, Machine Learning

Iambic Therapeutics

ML Software Engineer (I/II) developing and operating ML systems for drug discovery at Iambic Therapeutics. Collaborating in a hybrid role with a multidisciplinary team in Boston, MA.

Posted 6/8/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesMid-LevelSenior💰 $129,600 - $190,000 per yearWebsite

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Hard Skills

machine learning workflowsPython developmentMLOps best practicesproduction servicesmodel lifecycledata toolingcloud deploymentcontainerizationinfrastructure as codeGPU workload considerations

Soft Skills

collaborationcommunicationmentoringcode reviews

Tools & Technologies

PyTorchHugging FacevLLMTritonONNX RuntimePandasArrowS3ParquetPrefect

Industry Keywords

scientific fielddrug discoverycross-functional teams

Tech Stack

Tools & technologies

AirflowAWSCloudPandasPythonPyTorch

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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; PhD with 0-3 years of experience 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.

Benefits

Comp & perks

company paid healthcare
flexible spending accounts
voluntary life insurance
401K matching
uncapped vacation