AI/ML Engineer Precision Oncology

Moffitt Cancer Center; Tampa (FL); On-site; USD 108,000 - 165,000; Full time

Job summary

Moffitt Cancer Center in Tampa, Florida, is seeking an AI/ML Engineer for Precision Oncology. You will design, deploy, and scale AI and machine learning systems to support cancer research and clinical outcomes optimization.

The role collaborates with AI Data Scientists, clinicians, and informaticians to translate cutting-edge AI into robust, production-ready solutions. Candidates should have strong Python, ML engineering, cloud experience, and a passion for improving patient care.

Qualifications

• Master's degree in CS/Engineering/Data Science or related field.
• At least 3 years of professional experience building and deploying ML systems.
• Strong Python programming and software engineering skills.
• Experience with PyTorch, Hugging Face, or similar frameworks.
• Experience with cloud platforms, data pipelines, and MLOps.

Responsibilities

• Design, develop, deploy, and maintain scalable AI/ML systems for precision oncology.
• Build AI platforms integrating multimodal clinical and research data.
• Develop data pipelines, training workflows, and inference services.
• Apply MLOps practices including versioning, monitoring, and governance.
• Collaborate with scientists and clinicians to translate methods into production solutions.

Skills

Python

Machine learning engineering

Data pipelines

Cloud computing

MLOps

Git

Docker

Kubernetes

Hugging Face

Foundation models

Education

Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, AI, Biomedical Engineering, Informatics

Bachelor's degree with relevant experience

Tools

Hugging Face

PyTorch

Docker

Kubernetes

Job description

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer. As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Join a dedicated team of nearly 11,000 who are shaping the future we envision. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and is continually named one of the Tampa Bay Times’ Top Workplaces.

Summary The AI/ML Engineer - Precision Oncology develops, deploys, and scales advanced artificial intelligence technologies for precision oncology. This role builds and manages the software platforms, data pipelines, computational infrastructure, and machine learning systems required to support AI-enabled cancer research and clinical outcome optimization initiatives.

The AI/ML Engineer works at the intersection of machine learning engineering, multimodal data integration, foundation models, generative AI, biomedical data science, and cancer research. This position collaborates closely with AI Data Scientists, clinicians, and informaticians to translate innovative AI methodologies into robust, reproducible, and institutionally scalable solutions for oncology applications.

Other related duties as assigned by appropriate Leadership.

Join Moffitt Cancer Center's Precision Oncology and AI initiatives as an AI/ML Engineer and help transform groundbreaking research into scalable, real-world solutions. This role sits at the intersection of machine learning engineering, multimodal data integration, generative AI, biomedical data science, and oncology, building the platforms, pipelines, and AI systems that accelerate cancer research and improve patient outcomes.

About the Lab Our mission is to improve cancer patient outcomes through AI-enabled precision oncology and clinical decision support. We develop and deploy multimodal AI approaches that integrate clinical, imaging, pathology, molecular, genomic, and longitudinal outcomes data to generate actionable insights that support personalized cancer care.

Working at the intersection of clinical care, translational research, and artificial intelligence, our team collaborates directly with oncologists, radiologists, pathologists, surgeons, nurses, and multidisciplinary care teams to develop solutions that address real-world challenges in cancer diagnosis, treatment planning, response assessment, and survivorship.

By translating advances in machine learning, real-world evidence, and multimodal AI into clinically meaningful applications, we strive to deliver the right information to the right clinician at the right time, helping improve outcomes and advance the future of precision oncology.

Position Highlights

• Design and deploy enterprise-scale AI and machine learning systems that support cancer research and AI-enabled clinical outcome optimization initiatives.
• Work with cutting-edge technologies including foundation models, large language models (LLMs), multimodal AI systems, and generative AI applications.
• Develop scalable AI platforms integrating clinical, imaging, pathology, molecular, genomic, and outcomes data.
• Collaborate with AI Data Scientists, clinicians, and informaticians to deliver innovative solutions with real-world impact across oncology research and healthcare.

The Ideal Candidate

• Passionate about building robust AI systems that advance scientific discovery and improve patient outcomes.
• Brings a strong understanding of real-world oncology data, with experience working across clinical and translational cancer datasets and an appreciation for the challenges of developing AI solutions that support clinical decision-making and improve patient outcomes.
• Experienced in machine learning engineering, software development, cloud computing, and scalable data infrastructure.
• Thrives in a collaborative environment and enjoys transforming complex research concepts into production-ready applications.
• Keeps pace with emerging AI technologies and is excited to help shape the future of precision oncology.

Responsibilities

• Design, develop, deploy, and maintain scalable AI and machine learning systems for precision oncology applications.
• Build and manage AI platforms that integrate multimodal clinical and research datasets.
• Develop scalable data pipelines, model-training workflows, inference services, and software infrastructure supporting AI initiatives.
• Implement machine learning operations (MLOps) best practices, including model versioning, experiment tracking, deployment, monitoring, and governance.
• Develop and optimize foundation models, generative AI solutions, large language models (LLMs), vision‑language models (VLMs), and other AI applications.
• Create APIs, software services, and user‑facing applications that integrate AI capabilities into research, clinical, and operational environments.
• Evaluate and implement emerging AI technologies, engineering frameworks, and best practices that support institution‑wide AI innovation.
• Collaborate closely with scientists, clinicians, and technical teams to translate novel AI methodologies into scalable solutions.

Credentials and Qualifications

• Required: Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Artificial Intelligence, Biomedical Engineering, Informatics, or a related quantitative discipline.
• Bachelor's degree may be considered with additional relevant experience.
• Three (3) years of professional experience developing and deploying machine learning systems, data platforms, or AI‑enabled software solutions.
• Relevant experience may be gained through master's degree research.
• Strong software engineering and programming skills in Python.
• Experience developing and deploying machine learning and deep learning applications using PyTorch, Hugging Face, or similar frameworks.
• Experience building large-scale data processing pipelines and supporting AI systems in cloud, HPC, GPU, or distributed computing environments.
• Experience with MLOps, Git, containerization technologies, and production‑grade AI software development.
• Preferred Experience with foundation models, LLMs, vision‑language models (VLMs), multimodal AI systems, or generative AI applications.
• Experience integrating clinical, imaging, pathology, molecular, genomic, and outcomes data into AI solutions.
• Experience with cloud‑native AI platforms and services.
• Experience with CI/CD pipelines, workflow orchestration, infrastructure automation, and AI governance best practices.
• Experience with vector databases, semantic search, retrieval‑augmented generation (RAG), retrieval systems, or agentic AI frameworks.

Moffitt Cancer Center Location

Moffitt Cancer Center is an NCI-designated Comprehensive Cancer Center in Tampa, Florida.

Tampa is an ideal choice for those seeking opportunities in a rapidly growing metropolitan city.

With its vibrant economy, diverse culture, and year‑round sunshine, Tampa Bay offers an exceptional quality of life and a thriving innovation ecosystem.

Join the many professionals who have discovered why Tampa is one of the fastest‑growing metropolitan areas in the United States.

Moffitt Team Members

• Eligible for an annual Team Member Incentive.
• Eligible for an annual Team Member Merit Increase.
• Offered a comprehensive benefits package including health, financial, and lifestyle coverage.

Salary Range

Salary Range $108,492.80 - $165,422.40 Salary ranges posted for this position represent the expected base pay range for the role. Actual compensation may vary based on location and a variety of job-related factors, including experience, skills, education, and internal equity among Team Members in similar positions. We are committed to maintaining fair and equitable pay practices and regularly review compensation to ensure alignment across our workforce.

Equal Employment Opportunity

Moffitt Cancer Center is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or protected veteran or disabled status. We seek candidates whose skills, and personal and professional experience, have prepared them to contribute to our commitment to diversity and excellence.

Reasonable Accommodation

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