Sr. AI/ML Engineer I (6475)

About the role

As 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.

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.

Requirements

• Active Secret security clearance
• Bachelor's degree in Computer Science, Engineering, Data Science or related technical discipline.
• 4+ years of experience building and managing ETL and ELT data pipelines within Databricks environment
• Hands-on experience with Python and SQL and libraries such as TensorFlow, PyTorch, Scikit-learn
• Experience deploying models on cloud platforms (such as AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)
• Experience managing model deployment and monitoring (MLOps, MLflow, Kubeflow, etc.)
• Knowledge of data modeling, neural network architectures, and software development and CI/CD best practices
• Willing/able to travel to customer, as needed

Pay

Salary range: $138,000 - $184,000. The final salary is based on qualifications, skills, and relevant experience, and may include performance‑based bonuses, company‑paid training and/or certifications, and referral bonuses.

Benefits

• Health, dental, and vision insurance
• 401(k) retirement plan with company match
• Paid time off (PTO) and holidays
• Parental leave and dependent care
• Flexible work arrangements
• Professional development opportunities
• Employee assistance and wellness programs