Software Engineer II – Machine Learning Systems, Productization

. Work embedded with ML scientists to co-develop and refine model training and evaluation workflows .

Posted 4/23/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesSeniorLead💰 $152,000 - $190,000 per yearWebsite

Tools & technologies

AWSCloudKubernetesPython

Key responsibilities & impact

Work embedded with ML scientists to co-develop and refine model training and evaluation workflows
Translate experimental research code into maintainable, well-structured, and reusable systems
Build and expand benchmarking systems for running models on structural and affinity datasets, computing metrics, and supporting reproducible evaluation
Enable rapid iteration by developing tooling and interfaces that expose new capabilities to researchers
Contribute to the ongoing development and productization of NeuralPLexer
Collaborate with platform and infrastructure engineers on scaling workflows where needed, without owning core infrastructure
Perform code reviews and actively mentor best practices in software engineering across the team
Improve reliability, clarity, and reproducibility of ML workflows and supporting systems
Communicate technical work effectively across a cross-functional research and engineering team

What you’ll need

8+ years of software engineering experience (or equivalent)
Strong Python skills and demonstrated rigor in software engineering practices (testing, versioning, code quality)
Experience working closely with ML practitioners or in research-driven environments
Experience building or supporting ML workflows, data pipelines, or evaluation systems
Ability to operate in partially defined, research-heavy environments and bring structure to evolving codebases
Strong collaboration skills and comfort with pair programming and iterative development
Experience with scientific or computational research environments (preferred)
Familiarity with structural biology, chemistry, or molecular modeling workflows (preferred)
Exposure to cloud-based systems (e.g., AWS, Kubernetes) and/or HPC (preferred)
Experience working with large-scale or heterogeneous datasets (preferred)

Comp & perks

ATS Keywords

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Hard Skills & Tools

Pythonsoftware engineering practicestestingversioningcode qualityML workflowsdata pipelinesevaluation systemscloud-based systemsHPC

Soft Skills

collaborationpair programmingiterative developmentmentoringcommunication