Machine Learning Engineer (Applied ML/MIssion Systems) - R133

Expedition Technology•Herndon, VA

About The Position

Expedition Technology (EXP) is seeking a Machine Learning Engineer to join a fast-paced, high-visibility development program focused on rapidly maturing into an operational capability. In this role, you will design, prototype, and iterate on machine learning models and data pipelines that address real-world mission problems. The work is focused on temporal, geospatial, and track-based data, enabling advanced analytics and decision support in complex environments. This effort is an active development program that must demonstrate measurable progress quickly to enable transition. The ideal candidate is comfortable working in this type of environment: building, testing, and refining approaches under tight timelines while steadily moving capabilities toward production readiness. We’re looking for engineers who bridge the gap between machine learning research and deployable systems—someone who can experiment, iterate, and incrementally operationalize models in secure, cloud-native environments.

Requirements

U.S. Citizenship
Active TS/SCI clearance
5+ years of experience in machine learning, data engineering, or backend software engineering
Strong programming skills in Python
Experience developing or supporting machine learning models in production environments
Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow, or similar)
Familiarity with data processing and analysis (NumPy, Pandas, etc.)
Understanding of core ML concepts (supervised/unsupervised learning, feature engineering, evaluation)
Experience with cloud environments (AWS preferred)
Familiarity with Docker, Kubernetes, or other containerized systems
Experience working with Linux environments
Knowledge of Git and modern software development practices (SDLC, CI/CD)

Nice To Haves

Experience working with track, time-series, or geospatial data
Familiarity with maritime domain data or analytics
Understanding of probabilistic modeling, filtering, or tracking algorithms (e.g., Kalman filters, multi-object tracking)
Experience building end-to-end ML pipelines (data ingestion → training → deployment → monitoring)
Exposure to distributed data processing frameworks
Experience deploying ML systems in classified or mission environments

Responsibilities

Design, develop, and deploy machine learning models and pipelines for real-world mission applications
Work with temporal and track-based datasets (e.g., entity tracking, time-series, geospatial data)
Build data processing and feature engineering workflows to support model training and evaluation
Operationalize models using containerized, cloud-native infrastructure (AWS, Docker, Kubernetes)
Collaborate with engineers and analysts to translate mission needs into ML-driven solutions
Develop and integrate APIs and services that expose model outputs to downstream systems
Optimize models and pipelines for performance, scalability, and reliability
Contribute to experimentation frameworks, model evaluation, and continuous improvement workflows
Participate in Agile development, code reviews, and engineering best practices

Benefits

Company-paid, medical, dental and vision insurance
Up to 45 days of PTO
12% 401k match - Traditional and Roth options available
Student loan repayment assistance
Paid Family Leave
Tuition Reimbursement - $5250/year available
Referral bonus program
Free tickets to sporting events, theater, concerts and more
Free, onsite fitness center, onsite cafeteria with reduced-cost meals
A collaborative, creative and supportive culture where you will be encouraged to push boundaries, take risks and enjoy the rewards.