Health Science AI and ML Engineer

Health Science AI and ML Engineer page is loaded## Health Science AI and ML Engineer locations:
Bethesda, MD:
Atlanta, GAtime type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
May 17, 2026 (30+ days left to apply) job requisition :
R0234211

Health Science AI and ML Engineer
*
* The Opportunity:

** As a Scientific AI and ML Engineer on our team, you’ll apply your deep technical expertise to create innovative AI and ML algorithms, frameworks, and tools to address complex scientific challenges. You’ll collaborate with a multidisciplinary Agile development team to develop, validate, and optimize AI and ML models and workflows. Whether it’s designing novel algorithms, enabling automation of AI workflows, or scaling solutions in a cloud environment, you’ll have the opportunity to pioneer new approaches while improving scientific outcomes.

As a critical member of the team, you’ll identify opportunities for leveraging AI and ML to solve real-world problems, guide efforts to mitigate risks, optimize resources, and improve lives.

Work with us to apply the power of AI and ML to solve scientific problems at the intersection of health and technology, and protect America from health, safety, and security threats.
** What You’ll Work On:
*** Develop and optimize novel AI and ML algorithms tailored to scientific challenges, integrating domain knowledge to ensure results are actionable and relevant.
* Design, validate, and deploy end-to-end AI and ML workflows in cloud environments to address complex analytical needs across the organization.
* Collaborate with cross-functional teams to design efficient frameworks for data preparation, feature engineering, model selection, and outcome interpretation across data sources.
* Build tools and infrastructure to enable seamless experimentation, rapid model iteration, and reproducibility of scientific AI and ML experiments.
* Scale AI and ML solutions using advanced techniques such as distributed computing, cloud environments, including Azure and Databricks, and containerized deployments.
* Implement automated pipelines for training, validating, and deploying models into production with rigorous monitoring and evaluation processes.
* Develop containerized applications and APIs for exposing AI and ML model capabilities, ensuring accessibility and interpretability for stakeholders.
* Identify and introduce state-of-the-art AI and ML techniques and tools such as explainable AI (XAI), reinforcement learning, and probabilistic modeling, to enhance research outcomes and operational decision-making.
* Support collaboration with data scientists, researchers, and engineers to bridge the gap between foundational AI and ML research and deployed, impactful applications.

Join us. The world can’t wait.
** You Have:
*** 5+ years of experience in bioinformatics or computational biology, including analysis and processing of biological and imaging data, such as FASTQ, BAM, CRAM, VCF, or DICOM
* 3+ years of experience across data science, AI, and data engineering with ownership of end-to-end analytical or ML solutions
* Experience designing and deploying AI and ML solutions, including model training, evaluation, and production
* Experience with cloud-based AI platforms, including Databricks, AWS, or Azure ML
* Knowledge of Python or R for data analysis, modeling, and pipeline development
* Ability to translate complex biological questions into analytical approaches and apply existing methods to novel datasets
* Ability to work independently, lead technical initiatives, and deliver in a fast-paced, evolving environment
* Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
* Bachelor’s degree in a Science field
** Nice If You Have:
*** Experience with PySpark or SparkR
* Experience with Kubernetes or another container management system for managing containerized AI and ML workloads
* Experience designing and implementing automated, reproducible data, and ML pipelines in a cloud environment
* Experience with version control tools, including Git
* Knowledge of AI model explainability, ethical AI, or advanced deep learning frameworks, such as Tensor…