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Your Impact Own your opportunity to work alongside federal civilian agencies. Make an impact by providing services th...

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Selected role

AI ML Engineer

General Dynamics Information Technology Washington, DC, US

$128k - $173k Senior Full-time

Your Impact

Own your opportunity to work alongside federal civilian agencies. Make an impact by providing services that help the government ensure the well being and support of U.S. citizens.

Job Description

The AI/ML Engineer is responsible for designing, developing, and implementing machine learning models and artificial intelligence solutions to solve complex problems, optimize processes, and enhance decision-making. They work closely with data scientists and software engineers to build scalable, efficient systems while leveraging advanced algorithms and large datasets.

Design, develop, implement and use machine learning algorithms and models to address business challenges and opportunities, such as predictive analytics, natural language processing, computer vision and recommendation systems.
Collect, clean, and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality, integrity and relevance for model training and evaluation.
Train, validate, and optimize machine learning models using state-of-the-art techniques and frameworks. Evaluate model performance, interpret results, and iterate on model design as needed.
Extract, select, and engineer relevant features from raw data to improve model performance and generalization capabilities. Utilizes domain knowledge and data exploration techniques to identify informative features.
Deploy machine learning models into production environments, integrating them with existing systems and applications. Implements scalable, efficient, and reliable solutions for real-time batch inference.
Monitor model performance, reliability, and scalability in production environments, implementing automated monitoring and alerting systems to detect anomalies and performance degradation.
Document technical designs, implementation details, and best practices for AI solutions.
Collaborate with cross-functional teams to include data scientists, software engineers, product managers, and other stakeholders to understand requirements, prioritize projects and delivery impactful AI Solutions.
Perform additional duties as assigned.
May coach and provide guidance to less experienced professionals.
May serve as a team or task lead.
Works independently under general supervision

To qualify, you must meet these basic qualifications:

Required Skills

Bachelor’s degree in relevant field and 5+ years of experience
Analytical & Programming
Strong Python (data manipulation, model development; libraries like Pandas, NumPy, scikit-learn).
SQL proficiency (joins, window functions, performance-aware queries).
Statistical foundations (probability, hypothesis testing, regression, experimental design/A-B testing).
Data Modeling
End-to-end ML workflow experience (feature engineering, training, validation, deployment, monitoring).
Data wrangling & ETL/ELT (building reliable pipelines; handling messy, large datasets).
Model evaluation (metrics selection, bias/variance trade-offs, error analysis).
AI Integration w/ MLOps
Hands-on API integration for AI services (e.g., calling model endpoints, building microservices).
Production deployment of models (packaging, versioning, CI/CD for ML).
Model monitoring (drift detection, performance tracking, retraining triggers).
Cloud Platforms
Experience with at least one major cloud (Azure, AWS, or GCP) for data/AI workloads.
Familiarity with containers (Docker) and source control (Git).
Data visualization skills (Power BI or Tableau) to communicate insights and outcomes.
Communication
System analysis skills to identify viable AI insertion points in processes, products, or workflows.
Stakeholder communication (translating technical findings into business value and concrete recommendations).
Documentation of models, assumptions, data lineage, and decisions.
Governance/Security
Responsible AI awareness (fairness, explainability, privacy, and compliance considerations).
Basic understanding of data security and access controls in production environments.

Preferred Skills

Advanced AI/LLM
Experience with LLMs (e.g., Azure OpenAI Service/OpenAI API) for summarization, classification, or copilots.
Prompt engineering and evaluation of LLM outputs for quality and safety.
RAG pipelines (retrieval-augmented generation), vector databases (e.g., Azure AI Search, Pinecone, FAISS), and embeddings.
Fine-tuning or model adaptation strategies for domain-specific use cases.
MLOps Engineering
Model orchestration/experiment tracking (MLflow, Weights & Biases).
Kubernetes and ML deployment tools (e.g., AKS/EKS, Argo, KServe).
Feature stores, A/B testing frameworks, and event-driven/streaming data (Kafka, Kinesis).
CI/CD pipelines (GitHub Actions, Azure DevOps) and Infrastructure as Code (Terraform, Bicep).
Data Platform Integration
Databricks, Snowflake, or BigQuery experience.
Building robust APIs (REST/GraphQL) and microservices around models.
Monitoring & Observability (Prometheus, Grafana; app & model logs).
Responsible AI & Compliance
Practical experience with model risk management, documentation standards, and explainability (SHAP, LIME).
Knowledge of privacy-by-design and PII handling (data minimization, anonymization).
(If applicable to the environment) familiarity with FedRAMP or regulated environments.
Additional Languages/Tools
R, PySpark, or Scala for data-intensive workloads.
LangChain or Semantic Kernel for LLM app development.
Tableau/Power BI advanced (parameterized dashboards, Row-Level Security).
Ability to support 24x7 environment for business critical and contractual SLA impacting issues

Clearance: Candidates must be eligible to obtain a federal security clearance

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
Flexibility: Full-flex work week to own your priorities at work and at home
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.

Work Requirements

Years of Experience

5 + years of related experience

may vary based on technical training, certification(s), or degree

Certification

Travel Required

None

Salary and Benefit Information

The likely salary range for this position is $128,039 - $173,229. 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.

View information about benefits and our total rewards program.

About Our Work

We are GDIT. A global technology and professional services company that delivers technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 30,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across over 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, cloud, cyber and application development. Together with our customers, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.

Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc.

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

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