Mission-Centric AI/ML Systems Engineer — TS/Poly

Saic

Chantilly (VA)

On-site

USD 160,000 - 200,000

Full time

6 days ago

Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Job summary

SAIC is seeking a highly skilled AI/ML Systems Engineer to provide Systems Engineering and Technical Advisory (SETA) support for a mission-critical program in Chantilly, VA, with occasional locations in El Segundo, CA or Cape Canaveral, FL.

The role focuses on shaping AI/ML strategy, driving innovation, and ensuring delivery of cutting-edge capabilities while working with cross-functional teams and maintaining an active Top Secret clearance with Polygraph.

Qualifications

Bachelors and nine (14) years or more experience; Masters and seven (9) years or more experience; PhD or JD and four (4) years or more experience.
Active Top Secret Clearance with Polygraph.
Experience designing and implementing AI/ML solutions.
Strong knowledge of ML frameworks (e.g., TensorFlow, PyTorch) and programming languages (e.g., Python, R).
Experience with cloud computing services (e.g., AWS, Azure, Google Cloud) and their AI/ML offerings.
Proficient in data modeling, data pipeline creation, and deployment of ML models in production.
Familiarity with DevOps practices, including MLOps, and CI/CD pipelines for AI/ML.
Must have SECURE Plus Certification.

Responsibilities

Collaborate with cross functional teams to define AI/ML project goals, success criteria, and development roadmaps that align with mission priorities.
Understand and guide the design of advanced AI/ML models and algorithms, ensuring solutions address complex mission challenges and deliver measurable value.
Translate mission and business challenges into AI/ML opportunities, clearly articulating benefits, risks, and trade offs to non technical stakeholders.
Stay current on emerging AI/ML technologies, introducing best practices, tools, and methodologies to strengthen the customer’s technical posture.
Provide mentorship and technical leadership to junior AI/ML practitioners, fostering a culture of innovation and continuous learning.
Work closely with customer and vendor data engineers and architects to ensure data pipelines, infrastructure, and compute environments are optimized for model development and deployment.
Support vendor teams in rigorous model validation and performance testing, ensuring AI/ML solutions meet mission requirements for accuracy, reliability, and robustness.