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

Expedition Technology; Herndon (VA); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Company-paid medical, dental and vision insurance

Up to 45 days of PTO

12% 401k match – Traditional and Roth options available

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

Job summary

Expedition Technology in Herndon, Virginia, is seeking a Machine Learning Engineer to join a fast-paced development program focused on delivering operational capabilities. You will design and develop machine learning models and pipelines for real-world mission applications, leveraging geospatial and track-based data.

The ideal candidate should have over five years of experience in machine learning and backend engineering, with strong programming skills in Python, and familiarity with cloud environments like AWS. Comprehensive benefits include medical insurance, 401k matching, and generous PTO.

Qualifications

• 5+ years of experience in machine learning, data engineering, or backend software engineering.
• Active TS/SCI clearance required.
• Understanding of supervised/unsupervised learning and evaluation.

Responsibilities

• Design, develop, and deploy machine learning models and pipelines.
• Operationalize models using containerized, cloud-native infrastructure.
• Collaborate with engineers and analysts to translate mission needs into ML-driven solutions.

Skills

Machine learning frameworks (e.g., PyTorch, TensorFlow)

Strong programming skills in Python

Data processing and analysis (NumPy, Pandas)

Experience with Docker

Experience with Kubernetes

Experience working with Linux environments

Tools

AWS

Git

Containerized systems

Job description

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.

What You'll Do

• 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

Required Qualifications

• 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)
• 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)

Preferred / Nice‑to‑Have

• 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

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.

EXP is proud to be an Equal Opportunity Employer that believes a diverse range of talent creates an environment that fosters creativity and innovation. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, genetic information, or protected veteran status.