AI/ML Engineer

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

BI Full 6C (T4)

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

Actionable Insights, Data Analysis, Data Analytics

Certifications:

None

Experience:

10 + years of related experience

US Citizenship Required:

No

Job Description:

AI/ML ENGINEER SME

Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As an AI/ML Engineer SME at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward.

MEANINGFUL WORK AND PERSONAL IMPACT

Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program.

GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The AI/ML Engineer will be part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program.

The successful candidate will be responsible for delivering advanced analytics, visualizations, statistical modeling, and AI/ML capabilities; including Generative AI and Agentic AI solutions, predictive models, forecasting, and advanced analytics; that provide data-driven decision-support tools and actionable insights to users and stakeholders of the CMM application. This role provides technical leadership, strategic guidance, and tool recommendations to accelerate product development, and improve decision automation and overall CMM products. The role also oversees design, development, integration, and continuous enhancement advanced analytics and AI/ML capabilities in alignment with strict federal compliance requirements.

THE AI/ML ENGINEER WILL EXECUTE THE FOLLOWING RESPONSIBILITIES

AI/ML & Advanced Analytics

• Define and execute AI/ML strategy aligned to CMM modernization objectives.
• Design, develop, deploy, and maintain ML, predictive, forecasting, Generative AI, Agentic AI, and advanced analytics solutions.
• Build and tune models using appropriate algorithms, architectures, and data pipelines.
• Develop LLM-powered applications, RAG pipelines, AI agents, and intelligent automation capabilities.
• Apply statistical and advanced analytics methods to support data-driven decision-making.
• Evaluate foundation models, commercial/open-source models, and emerging AI technologies.
• Create proof-of-concepts and transition successful models to production.
• Document AI/ML architecture, methodologies, features, and validation results.

MLOps / LLMOps / AI Operations

• Automate model deployment, monitoring, versioning, lineage, and lifecycle management.
• Build and maintain MLOps/LLMOps pipelines integrated with CI/CD and DevSecOps.
• Implement automated model training, testing, validation, deployment, rollback, and alerting.
• Monitor model performance, drift, and degradation; trigger retraining as needed.
• Maintain reproducible environments and support scalable cloud deployment.
• Integrate AI/ML pipelines with data engineering and cloud platform services.

Responsible AI & AI Governance

• Ensure compliance with Responsible AI requirements: transparency, fairness, explainability, security, and privacy.
• Perform bias assessments, model risk evaluations, and bias mitigation strategies.
• Conduct and document explainability assessments and model interpretability.
• Lead ATO impact analysis for AI/ML capabilities, support security, privacy, and authorization reviews.
• Maintain the AI/ML Capability Register, model cards, governance artifacts, and lifecycle documentation.
• Support AI/ML security assessments, privacy reviews, data classification assessments, and authorization activities.
• Identify risks such as hallucination, prompt injection, data leakage, misuse, and drift; implement safeguards and monitoring.
• Support federal AI, cybersecurity, privacy, and governance compliance.

Collaboration & Innovation

• Partner with analysts, engineers, architects, governance, cybersecurity, and business stakeholders.
• Translate business problems into AI/ML use cases and technical solutions.
• Assess data readiness and ensure appropriate data ownership, quality, and lineage.
• Develop standards, reusable patterns, and best practices for AI/ML development.
• Recommend AI/ML tools, cloud services, and SDLC automation opportunities.
• Mentor teams on AI/ML development and Responsible AI practices.
• Communicate technical findings clearly to both technical and non-technical audiences.

QUALIFICATIONS

• Education: BA/BS or equivalent required; MA/MS strongly preferred.
• Experience: 15+ years of general experience in information systems with at least 10+ of those years involving specialized experience required. Experience may be considered in lieu of degree as follows: HS (19+ years), AA/AS (17+ years), BA/BS (15+ years), MA/MS (13+ years), Doctorate Degree/Ph.D. (12+ years).
• Expertise in machine learning, deep learning, and natural language processing (NLP) techniques.
• Experience in AI/ML engineering, machine learning, data science, or advanced analytics.
• Strong proficiency with Python, SQL, ML/DL frameworks (TensorFlow, PyTorch, scikit-learn, XGBoost) and cloud AI services (AWS SageMaker, Bedrock, Azure ML, GCP Vertex AI).
• Experience implementing MLOps pipelines and integrating ML workflows into CI/CD environments.
• Knowledge of federal compliance frameworks such as FedRAMP, FISMA, and NIST AI RMF.
• Understanding data governance, model monitoring, and ethical AI practices.
• Strong analytical, advisory, and communication skills to bridge strategy, engineering, and business outcomes.
• Experience leading federal or judiciary AI/ML modernization programs (Preferred).
• Familiarity with Generative AI for content generation, summarization, and development assistance.
• Experience applying predictive analytics to performance monitoring, test optimization, and resource planning.
• Experience with vector databases, LLM fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines, prompt engineering, and/or Agentic AI architectures.
• Experience with MLOps/LLMOps (MLflow, SageMaker, Vertex AI, or Azure ML), model deployment, versioning, monitoring, and lifecycle management.
• Experience with Generative AI/LLM frameworks (LangChain, vector databases, OpenAI/Azure).
• Background in data visualization and explainable AI (XAI) methods (Preferred).

COMMUNICATION & ORGANIZATIONAL SKILLS

• Excellent presentation and communication skills.
• Consultant mindset with the ability to work with high level customer stakeholders and build excellent customer relationships.
• Experience identifying and applying industry tools, solutions, methods best practices, and emerging technologies.
• Strong analytical skills and problem-solving skills with the ability to formulate and communicate recommendations for improvement.
• Demonstrated ability to work effectively, independently, and as part of a team.

PREFERRED CERTIFICATIONS

One or more of the following certifications is preferred but not required.

• Data Visualization and Data Story Telling certifications
• Tableau Certified Data Analyst, Tableau Desktop Specialist
• Power BI Data Analyst
• Story Telling with Data
• Certified Data Management Professional (CDMP)
• Snowflake SnowPro Core
• Databricks Certified Data Professional
• AWS Certified Data Analytics - Specialty
• AWS Certified Solutions Architect - Professional
• AWS Certified Data Engineer
• AWS Certified Machine Learning - Specialty or Google Professional ML Engineer
• Certified AI Governance Professional (AIGP) or NIST AI RMF certification
• SAFe Architect (ARCH) or SAFe DevOps Practitioner (SDP)
• PMP or ITIL 4 Foundation

Security Clearance Level: Must be able to pass a background check to obtain a position of Public Trust.

Must be a US Person (Green Card Holder, US Permanent Resident Alien, Refugee, Asylee, or US Citizen).

Location: Remote.

GDIT IS YOUR PLACE

At GDIT, the mission is our purpose, and our people are at the center of everything we do.
● Growth: AI-powered career tool that identifies career steps and learning opportunities
● Support: An internal mobility team focused on helping you achieve your career goals
● Rewards: Comprehensive benefits and wellness packages, 401K with company match, and competitive pay and paid time off
● Community: Award-winning culture of innovation and a military-friendly workplace

OWN YOUR OPPORTUNITY

Explore a career in data science and engineering at GDIT and you’ll find endless opportunities to grow alongside colleagues who share your determination for solving complex data challenges.

The likely salary range for this position is $195,240 - $264,148. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

Less than 10%

Telecommuting Options:

Remote

Work Location:

Any Location / Remote

Additional Work Locations:

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development.Join our Talent Community to stay up to date on our career opportunities and events at

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Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

Originally posted on Himalayas