Collaborate with Agentic AI Scientists to build and securely deploy AI agents to automate and optimize labor intensive workflows
Support both R&D tasks and direct customer engagements to speed the transition delivery of novel applied research solutions onto direct contracts
Design, implement, and maintain tools that enable agent deployments using MLOps best practices in scalable cloud infrastructure
Develop and document processes that enable secure automated development and deployment of AI agents
Design, build, train, and evaluate Machine Learning models
Build repeatable Machine Learning pipelines for model training, evaluation, deployment, and monitoring
Perform R&D to enable AI Observability and performance metrics
Design, implement, and manage cloud resources for MLOps infrastructure
Operationalize production AI/ML systems by implementing model serving, monitoring, data and model drift detection, logging, and lifecycle management to ensure reliability, scalability, and maintainability
Work in a team of AI/ML researchers and engineers using Agile development processes

Requirements

Bachelor's degree in Computer Science, Engineering or related field and 2+ years of relevant experience, or a Master's degree with relevant experience
Bachelor's degree with 4+ years of experience or Master’s degree with 2+ years of experience in Computer Science, Machine Learning, Artificial Intelligence, or related discipline
Bachelor's degree with 8+ years of experience or Master’s degree with 6+ years of experience in Computer Science, Machine Learning, Artificial Intelligence, or related discipline
Bachelor's degree with 12+ years of experience or Master’s degree with 10+ years of experience in Computer Science, Machine Learning, Artificial Intelligence, or related discipline
Hands-on experience on building, automating, and managing AI/ML pipelines, and MLOps capabilities (Kubeflow, MLflow, etc.)
Advanced Python programming skills
Experience with AI/ML tools, such as common python packages (e.g., scikit-learn, TensorFlow, PyTorch) and Jupyter notebooks
Experience with MLOps tools and frameworks, such as Kubeflow, MLflow, DVC, TensorBoard
Experience with Software Development tools, including Git, containerization technologies (e.g., Docker), CI/CD frameworks
Experience with automated deployment pipelines for Agentic AI Models
Competence in troubleshooting and mitigating issues with prototyped and deployed AI
Demonstrated ability to orchestrate ML pipelines
Ability and willingness to obtain a Secret security clearance

Benefits

Health and Wellness programs
Income Protection
Paid Leave
Retirement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningArtificial IntelligenceMLOpsPythonAI ObservabilityModel ServingData Drift DetectionModel Drift DetectionAutomated Deployment PipelinesAgile Development

Soft Skills

CollaborationProblem SolvingCommunicationTeamworkTroubleshooting

Certifications

Bachelor's degree in Computer ScienceMaster's degree in Computer ScienceSecret security clearance