AI/ML Engineer Precision Oncology
Actively Hiring
Full-time $131k - $201k Posted 17 days ago
Responsibilities
- check_circle Design, develop, deploy, and maintain scalable AI and machine learning systems for precision oncology applications.
- check_circle Build and manage AI platforms that integrate multimodal clinical and research datasets.
- check_circle Develop scalable data pipelines, model-training workflows, inference services, and software infrastructure supporting AI initiatives.
- check_circle Implement machine learning operations (MLOps) best practices, including model versioning, experiment tracking, deployment, monitoring, and governance.
- check_circle Develop and optimize foundation models, generative AI solutions, large language models (LLMs), vision-language models (VLMs), and other AI applications.
- check_circle Create APIs, software services, and user-facing applications that integrate AI capabilities into research, clinical, and operational environments.
- check_circle Evaluate and implement emerging AI technologies, engineering frameworks, and best practices that support institution-wide AI innovation.
- check_circle Collaborate closely with scientists, clinicians, and technical teams to translate novel AI methodologies into scalable solutions.
- check_circle 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.
- check_circle Bachelor's degree may be considered with additional relevant experience.
- check_circle 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.
- check_circle Strong software engineering and programming skills in Python.
- check_circle Experience developing and deploying machine learning and deep learning applications using PyTorch, Hugging Face, or similar frameworks.
- check_circle Experience building large-scale data processing pipelines and supporting AI systems in cloud, HPC, GPU, or distributed computing environments.
- check_circle Experience with MLOps, Git, containerization technologies, and production-grade AI software development.
Preferred qualifications
- 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.
- 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.
About the company
- check_circle Design and deploy enterprise-scale AI and machine learning systems that support cancer research and AI-enabled clinical outcome optimization initiatives.
- check_circle Work with cutting-edge technologies including foundation models, large language models (LLMs), multimodal AI systems, and generative AI applications.
- check_circle Develop scalable AI platforms integrating clinical, imaging, pathology, molecular, genomic, and outcomes data.
- check_circle Collaborate with AI Data Scientists, clinicians, and informaticians to deliver innovative solutions with real-world impact across oncology research and healthcare.
- check_circle Passionate about building robust AI systems that advance scientific discovery and improve patient outcomes.
- check_circle 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.
- check_circle Experienced in machine learning engineering, software development, cloud computing, and scalable data infrastructure.
- check_circle Thrives in a collaborative environment and enjoys transforming complex research concepts into production-ready applications.
- check_circle Keeps pace with emerging AI technologies and is excited to help shape the future of precision oncology.
Tags & Focus Areas
Fulltime Ai Ai Engineer Machine Learning
About Moffitt Cancer Center
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