The Senior Artificial Intelligence & Machine Learning Engineer I/Scientist I works within the Artificial Intelligence Operations and Services group (AIOS) in the Informatics & Analytics department of Dana-Farber Cancer Institute. This role provides hands-on expertise in machine learning, NLP, and computer vision to build reuseable and scalable AI/ML tools and pipelines to support Dana-Farber operations, research, and clinical practice.

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The role operates in a matrixed team environment, collaborating with client-facing leads, software engineers, product managers, project managers, project sponsors, and clients.

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The Informatics & Analytics department serves patients, present and future, by collaboratively building a sustainable informatics and analytics ecosystem of tools and services to support and grow the Institute’s research, clinical, and business missions. The AIOS group provides services related to AI, machine learning, computer vision, NLP, production deployment, cloud infrastructure, data engineering, project management standards, and data labeling.

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.

• Bachelor’s degree in a related field (Computer Science, Data Science, Engineering) required.
• Master’s degree preferred.
• 3 years of work experience in machine learning and AI required.
• Relevant lab work and research projects, teaching assistantships, internships, cooperative education programs undertaken during an advanced degree program may be considered toward qualifying work experience.
• Experience within a clinical or research environment preferred.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

• Plan, advise and execute on scalable practices for development, deployment, and long-term monitoring for AI solutions, ensuring a delivery that is built for scale, reliable telemetry tracking, informative monitoring and diagnosis of model drift, and cross-platform efficiency.
• Implement and maintain best-in-class data solutions, managing machine learning models from deployment to retirement, ensuring models are well organized, auditable, and continuously perform with the highest degree of accuracy.
• Develop CI/CD pipelines for models in cloud environments, including batch, online, streaming, and edge training/inference.
• Elicit functional requirements from end users and data science teams, utilizing methods such as user interviews, mockups, wireframes, end-to-end testing, prototypes, GUI designs, and use cases.
• Communicate status on various project/program efforts to multiple groups including the AIOS team, client-facing leads, project sponsors, business owners, and internal stakeholders.
• Mentor and provide guidance to junior and new team members.

At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are committed to having faculty and staff that offer multifaceted experiences. ÂCancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

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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.

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