Note: The job is a remote job and is open to candidates in USA. GDIT is a technology and professional services company delivering mission-focused technology solutions, including AI, cloud, cyber, and software development capabilities. The AI/ML Delivery Engineer designs, builds, and scales secure enterprise AI, machine learning, and data products across cloud environments, while providing technical leadership, solution architecture, governance, delivery oversight, and executive communication to support the NIH mission.
Responsibilities
- Architect and deliver end-to-end AI/ML and generative AI solutions across the full lifecycle, including data integration, feature engineering, model development, evaluation, deployment, monitoring, and continuous improvement
- Design scalable, secure, and governed AI/ML architectures that support enterprise data management, cloud-native services, distributed computing, and high-performance workloads
- Develop and deploy production-ready AI solutions using modern techniques for large language models, intelligent search, workflow automation, model evaluation, monitoring, and continuous optimization
- Integrate enterprise AI and cloud services with organizational data platforms, security controls, governance frameworks, and operational processes
- Deliver AI and machine learning solutions across a variety of domains, including natural language processing, computer vision, predictive analytics, intelligent search, multimodal AI, and other mission-focused applications, using industry-standard frameworks and tools
- Design secure application programming interfaces (APIs), integration services, data pipelines, and orchestration workflows that enable AI capabilities to be reliably consumed by enterprise systems and end users
- Serve as the AI/ML technical authority for cross-functional data science, engineering, platform, security, infrastructure, and business teams
- Lead architecture reviews, AI readiness assessments, performance benchmarking, and infrastructure trade-off analysis for large-scale cloud, GPU, and distributed data workloads
- Establish MLOps, LLMOps, and ModelOps practices for CI/CD, experiment tracking, model registry, prompt/model versioning, automated testing, deployment promotion, rollback, drift/quality monitoring, lineage, and cost optimization
- Define responsible AI controls for privacy, IAM, key management, audit logging, PHI/PII handling, explain ability, model cards, bias/risk assessment, human oversight, and agentic guardrails
- Mentor engineers and data scientists while communicating complex AI concepts through clear solution narratives, architecture diagrams, demonstrations, and executive-ready materials
- Support solutioning activities by shaping technical approaches, estimating delivery patterns, and contributing to client responses
Skills
- Analytics, End-to-End Testing, Solution Architecture
- 10 + years of related experience
- Master of Science in Computer Science, Information Technology, Engineering, Mathematics/Statistics, Bioinformatics, Data Science, or equivalent professional experience
- 10+ years of related experience
- Hands-on experience with modern enterprise data platforms and cloud-native data architectures, including distributed data processing, data governance, machine learning lifecycle management, and batch and streaming data pipelines
- Production experience developing, deploying, and supporting AI/ML and generative AI solutions, including intelligent search, large language model (LLM) applications, workflow automation, model serving, evaluation, monitoring, and continuous improvement
- Experience with modern machine learning and deep learning frameworks, libraries, and tools for developing, training, evaluating, and deploying AI/ML solutions
- Experience designing, deploying, and managing AI/ML solutions in one or more major cloud environments, including cloud-native AI services, identity and access management, networking, security, and infrastructure
- Experience working with large, complex, sensitive, or regulated datasets, including data integration, migration, quality management, analytics, visualization, and governance in government, healthcare, or other regulated environments
- Excellent written and verbal communication skills, with the ability to collaborate effectively with technical teams, business stakeholders, and executive leadership
- Must be able to obtain a Tier 3 Public Trust
- Must be a US Person
- This position is fully remote; If selected, travel to NIH at applicant's expense will be required for onboarding
Benefits
- Fully remote position
- AI-powered career tool that identifies career steps and learning opportunities
- An internal mobility team focused on helping you achieve your career goals
- Comprehensive medical benefits, including a variety of medical plan options, some with Health Savings Accounts
- Dental plan options
- Vision plan options
- 401(k) plan with the ability to contribute both pre- and post-tax dollars up to IRS annual limits and receive a company match
- Full-flex work weeks where possible
- Vacation, sick, and personal time off
- Paid holidays
- Paid parental leave
- Paid military leave
- Paid bereavement leave
- Paid jury duty leave
- Typically 15 days of paid leave per calendar year for vacations, personal business, and illness
- An additional 10 paid holidays per year
- Up to 160 hours of paid family leave in a rolling 12-month period for eligible employees
- Short- and long-term disability benefits
- Life insurance
- Accidental death and dismemberment insurance
- Personal accident insurance
- Critical illness insurance
- Business travel and accident insurance
- Award-winning culture of innovation
- Military-friendly workplace
Company Overview