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Job Ref: JR-286 Location: 21 27 Burlington Ave, BOSTON, MA 02215 Category: IT/Informatics Employment Type: Full time ...

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Selected role

Senior AI-Machine Learning Engineer

Dana-Farber Cancer Institute Boston, MA, US

$121k - $129k Senior Full-time

Job Ref:

JR-286

Location:

21 27 Burlington Ave, BOSTON, MA 02215

Category:

IT/Informatics

Employment Type:

Full time

Work Location:

Boston Job Posting Location

Salary/Pay Rate:

$121,600.00 - $129,600.00 per year

Overview

The Senior 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.The Senior 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, disseminate innovative patient therapies and scientific discoveries around the world, and reduce 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.

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.

KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

Excellent communication and effective problem-solving skills

Track record in serving a variety of diverse customers and projects.

Ability to work independently, prioritize, and manage people if needed, adapting to meet the evolving needs of the Institute

Knowledge of MLOPS and ML engineering; GenAI and agentic AI; AL/ML and data science; data engineering and pipelines.

Proficiency with Python, R, Databricks, and/or Snowflake.

MINIMUM JOB QUALIFICATIONS:

Minimum Education:

Bachelor’s degree in a related field (Computer Science, Data Science, Engineering) required. Master’s degree preferred.

Minimum Experience:

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.

SUPERVISORY RESPONSIBILITIES: None

PATIENT CONTACT: None

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 who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply.

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.

EEO Poster

Pay Transparency Statement

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).

$121,600.00 - $129,600.00

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