Posting Description SOFTWARE ENGINEER / MACHINE LEARNING ENGINEER, MIT Jameel Clinic for Machine Learning in Health , to participate in the full life cycle of application and research-software development for Jameel Clinic research programs and related MIT collaborations. Responsibilities include requirements analysis, technical design, coding, testing, documentation, deployment support, troubleshooting, and production support for research workflows; developing and maintaining machine learning systems, data pipelines, model evaluation tools, applications, and reusable software components; supporting model training, evaluation, benchmarking, validation, analysis, and deployment-related workflows; working with health, biological, chemical, molecular, materials, and other scientific datasets; maintaining version-controlled repositories, testing practices, documentation, and coding standards; collaborating with faculty, researchers, students, technical staff, and external collaborators; evaluating relevant software tools, machine learning frameworks, data platforms, and engineering practices; and contributing technical material for reports, proposals, presentations, publications, and collaborator communications.
Job Requirements
REQUIRED : Bachelor's degree in computer science, engineering, machine learning, computational biology, computational chemistry, materials science, data science, or a related technical field; minimum five years of relevant programming, software engineering, machine learning engineering, research engineering, scientific computing, or applied data science experience; strong Python programming skills and experience with modern software development practices; experience with machine learning frameworks such as PyTorch, JAX, TensorFlow, or scikit-learn; experience developing technical design specifications, program specifications, prototypes, test scenarios, scripts, unit tests, and technical documentation; ability to work with structured and unstructured scientific datasets and translate technical requirements into maintainable code; strong analytical, debugging, documentation, communication, and collaboration skills; and ability to manage multiple technical tasks, follow through on priorities, and work both independently and as part of a team. PREFERRED : experience with molecular machine learning, biological data, chemical data, clinical data, materials data, graph-based methods, geometric deep learning, representation learning, generative models, or multimodal learning; familiarity with scientific data formats, APIs, databases, cloud computing, high-performance computing, Docker, workflow management, or MLOps practices; ability to read technical literature and translate research methods into working code; and experience contributing to collaborative research projects, open-source software, technical reports, proposals, or publications.
9/10/2026
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: RTL165931
- Position Id: 5f91d1563b3e07199b063ba0bd79c475
- Posted 30+ days ago
