AI Technical Lead – Cancer Research & Informatics

Leidos

Rockville (MD)

On-site

USD 131,000 - 237,000

Full time

14 days+

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Job summary

Leidos is recruiting a Technical Lead to guide AI-enabled solutions for NIH and NCI initiatives in cancer research and precision medicine. The role requires strategic technical leadership, cross‑disciplinary collaboration, and deep expertise in AI, ML, and biomedical informatics.

You will work with executive leadership and multidisciplinary teams to shape technology strategy, governance, and scalable deployments across cloud and HPC environments, ensuring secure, high‑quality outcomes for

Qualifications

Master's degree or higher in a relevant technical field.
15+ years of technical leadership in Federal health, biomedical research, or scientific computing.
10+ years designing and leading enterprise AI/ML solutions in healthcare or life sciences.
Experience with NIH, NCI, or federal biomedical research organizations.
Deep learning, ML, NLP, LLMs, computer vision, predictive analytics, and cloud-native AI architectures.
Experience advising senior government customers on AI strategy and enterprise architecture.
Proven leadership of multidisciplinary teams of AI/ML engineers and data scientists.
Experience with HPC, cloud-native AI platforms, Kubernetes, DevSecOps, and MLOps.
Familiarity with TensorFlow, PyTorch, Scikit-learn, Hugging Face, MLflow, Kubeflow, LangChain, vector and graph databases.
Ability to obtain and maintain a Public Trust / ADPII Clearance.

Responsibilities

Lead the technical strategy, architecture, and implementation of AI-enabled solutions for cancer research and precision medicine.
Advise NCI leadership on AI, ML, biomedical informatics, and digital modernization initiatives.
Collaborate with stakeholders to define priorities, evaluate technologies, and deliver mission-focused AI systems.
Oversee AI model development, deployment, lifecycle management, and MLOps practices.
Guide scalable AI and cloud-based architectures using HPC and multiple cloud providers.
Ensure Responsible AI: governance, explainability, bias mitigation, security and privacy.
Communicate complex concepts to Government executives, researchers, and business stakeholders.
Mentor engineering teams including AI engineers, data scientists, and cloud architects.
Evaluate emerging AI technologies to accelerate discovery and improve operational efficiency.