Apply a thorough understanding of data networks, databases, and cloud architecture to collect, gather, process, store, and provide timely data that feeds the data-driven decision process. Work with DoD relationships to establish data pipelines that support 1MDTF analytical requirements. Provide cloud-related data flow engineering services, including paths, staging, scheduling, and data ingestion. Establish Extract, Transform, Load (ETL) capabilities for data flow. Proficiency in software programming and development ecosystems, such as R & Python, and their relevant libraries. Experience with cloud tools, including Azure products like Power BI and Data Factory. Knowledge of relational databases and query languages such as Structured Query Language (SQL). Knowledge in data operations by ensuring data meets VAULTIS standards, ultimately achieving data-centricity by using speed and scale for operational advantage and increased efficiency across the warfighting functions and Army operations. Skill with current data algorithms, data analysis tools, and techniques to efficiently process and transform data into an analyzed format. Web programming skills for Linux and/or Windows environments. Experience with briefing senior leaders on data-centric recommendations. Basic understanding of probability, statistics, and machine learning for data analysis and visualization.

Typical duties include:

Machine Learning Engineer

Infrastructure Design and Maintenance:

o    Collaborate with customers, machine learning, and data science teams to understand requirements.

o    Establish infrastructure based on requirements and constraints.

o    Supports Continuous Integration/Continuous Deployment (CI/CD) for ML models.

Cloud & Data Pipeline Expertise:

o    Implement best practices for model training, deployment, and monitoring.

o    Proficiency with cloud platforms (Azure, AWS, or Google Cloud).

o    Develop and optimize ML pipelines using Python/R and frameworks (e.g., PyTorch/TensorFlow, LLM).

o    Engineer ML model deployment and management within cloud environments.

Programming Languages:

o    Proficient in Python, R, SQL, and scripting.

o    Experience with Deep Learning platforms (e.g., PyTorch, TensorFlow, Jupyter Notebook).

o    Version control using Git.

Additional Skills:

o    Understanding of containerization (Docker, Kubernetes).

o    Ability to effectively collaborate with data scientists and engineers.

o    Ability to drive Machine Learning process to product incremental model improvements.

Problem-Solving and Statistical Knowledge:

o    Strong problem-solving skills as applied to Machine Learning issues.

o    Comfortable with data manipulation, analysis, and scripting.

Education:

o    Bachelor’s degree in computer science, operations research, or related STEM field.

Security Clearance:

o    Active Department of Defense Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance

Job Type: Full-Time, on-site

Benefits:

•     401(k) matching

•     Dental, Health & vision insurance

•     Paid time off

•     Professional development assistance