Sr. AI/ML Engineer I (6407)

MetroStar•Washington, DC

5h•$133,000 - $147,000

About The Position

As a Sr. AI/ML Engineer I, you’ll design, develop, and deploy machine learning solutions supporting secure, web-based applications in a dynamic, mission-focused environment. This role emphasizes applied AI, experimentation, and collaboration with cross-functional teams to deliver production-ready capabilities that evolve as mission needs change. We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers. If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline.
Active Secret security clearance (required).
4+ years of experience in data science, machine learning, or applied artificial intelligence.
Strong hands-on experience developing, training, and tuning AI/ML models using Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Experience selecting and applying appropriate modeling approaches (e.g., supervised, unsupervised, reinforcement learning, or hybrid methods) based on problem context.
Strong software engineering fundamentals including API design, clean architecture, testing, and Git-based workflows.
Ability to work effectively in ambiguous problem spaces, defining requirements, success metrics, and implementation steps as understanding evolves.
Experience integrating AI models into web-based or service-oriented platforms, working alongside DevSecOps engineering teams.
Solid understanding of the full AI lifecycle, including data preparation, experimentation, validation, deployment considerations, and ongoing model improvement.
Strong analytical and problem-solving skills, with sound judgment on when to prototype, iterate, or rethink an approach.

Responsibilities

Design, develop, implement, and fine-tune AI and machine learning models to support web-based applications in secure environments with evolving use cases..
Build and maintain data pipelines, training workflows, and experimentation environments to enable rapid model iteration and evaluation.
Evaluate model performance using quantitative and qualitative metrics (e.g., accuracy, robustness, stability, efficiency, generalization) and translate results into actionable improvements.
Analyze data, model outputs, and experimental results to recommend changes to algorithms, features, data sources, or system architecture.
Proactively identify and assess tools, frameworks, and technologies that best support platform goals, balancing performance, scalability, and maintainability.
Collaborate closely with software developers, data engineers, DevSecOps teams, and stakeholders to integrate AI capabilities into production systems.
Ensure AI and data science solutions are transparent, testable, and maintainable to support long-term operational use.
Communicate technical approaches, assumptions, tradeoffs, and results clearly to both technical and non-technical audiences, including during design reviews and demonstrations.