Principal AI-Machine Learning Engineer

The Principal Artificial Intelligence & Machine Learning Engineer I/Scientist I works within the Artificial Intelligence Operations and Data Science Services group (AIOS) in the Informatics & Analytics department of Dana‑Farber Cancer Institute – a teaching affiliate of Harvard Medical School.
Read the overview of this opportunity to understand what skills, including and relevant soft skills and software package proficiencies, are required.
The Principal Artificial Intelligence & Machine Learning Engineer I/Scientist I works in a team environment on both short‑term priorities identified by our top clinicians, as well as on long‑term institutional efforts that aim at revolutionizing the way the Institute conducts basic cancer research and provides best‑in‑class clinical oncology to our patients.
AIOS is part of the department serving some of the most prominent research and clinical programs at the Institute, from basic to translational research, to clinical deployment, and operationalization. The AIOS group encompasses expertise in AI, data science, machine learning, computer vision, NLP, production deployment, cloud infrastructure, data engineering, project management standards, and data labeling. Dana‑Farber Cancer Institute (DFCI) provides expert, compassionate, and equitable care to children, adults, and their families, while advancing the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases. DFCI trains new generations of clinicians and scientists, disseminates innovative patient therapies and scientific discoveries around the world, and reduces the impact of cancer, while maintaining a focus on those communities who have been historically marginalized.
Located in Boston and the surrounding communities, Dana‑Farber Cancer Institute is a leader in life‑changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high‑risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow’s physician/researchers, and we work with amazing partners, including other Harvard Medical School‑affiliated hospitals.
PhD preferred.
8 years of relevant experience required with Master’s degree or 7 years of relevant experience required with PhD. Deep machine learning & AI skills, at the interface with computer science. Python experience is required; Meeting and consulting with physician scientists requiring machine learning & AI support and designing plans and solutions, participating in their research activities, as well as supporting them in the grant writing, and leading research efforts when required.
Interpreting complex machine learning & AI information. Monitoring new developments in the field and having vision for staying at the cutting edge.
Recognizing and reporting problems with the machine learning & AI process and identifying solutions.
Ability to communicate and solve problems effectively, track record in serving a variety of diverse customers and projects and of leading teams.
Natural language processing or Computer vision technologies, Transformers, Adversarial / Generative models, JAX + Flex / Haiku, Vision Transformers, Federated learning, AutoML, Self‑supervised learning, Causal ML, Reinforcement learning, Infrastructure as Code, DataOps (versioning, lineage, and governance), AIOps & MLOps life cycle (from deployment to monitoring to retirement), explainable AI, batch/online/streaming/edge training/inference, fully reproducible and auditable ML practices, CI/CD for large language models and large vision models, Multi‑Cloud & Hybrid data platforms, productized Docker/Spark/Kubernetes solutions such as Databricks and Snowflake, High‑throughput big data processing under redundancy / low‑latency requirements.
As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff who offer multifaceted experiences. Dana‑Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.
The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications. For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).