Applied Machine Learning Engineer

Information Systems and Cyber Division (ISCD) staff couple the latest in information system technologies, such as elastic compute clouds, containerization, microservices, real-time operating systems, and visualization frameworks, with expertise in cyber security, software architecture, software engineering, data science, Artificial Intelligence, process improvement, and software development to deliver responsive, resilient, high-performance software intensive systems to our Intelligence Community, DoD, and civilian customers. 

The Data Science and Artificial Intelligence Department (DSAID) seeks a creative and enthusiastic Machine Learning Engineer to join a diverse team of engineers, data scientists, and programmers with a passion for researching, prototyping, understanding, and building AI and data enabled tools across the space enterprise.  We are a growing, innovative, and collaborative department that makes meaningful contributions to National Security Space (AF, NRO, etc.), and Civil and Commercial customers (NASA, MDA, DHS, etc.).   

This position is for the Data Science Applications section, where we focus on solving customer problems with digital applications that involve data science and machine learning techniques. DSA is looking for machine learning engineer with reinforcement learning and graph theory experience to support customers in the missile warning/missile tracking domain. 

This is a full-time position based in Colorado Springs, Colorado which requires 100% onsite work. 

What You’ll Be Doing  

DSAID’s customers range from National Security Space (AF, NRO, etc.) to civil (NASA, NOAA, etc.) and commercial (commercial space, autonomous vehicles, etc.) 

• DSAID applies data science and AI knowledge across the space enterprise, to Aerospace enterprise capabilities, and towards corporate workforce development and strategic focus areas 

• Machine Learning Engineers learn and develop their skills by working on teams spanning disciplines, experience levels, and organizational boundaries. 

• Primary functions include: 

• Evaluation of technologies for use in scalable and resilient mission-critical applications in a production environment 

• Coordinated development and execution of AI/ML experiments 

• Coordinated development of proof-of-concept infrastructure configuration and software prototypes 

• Collaboration with small, innovative teams to deliver features and products 

• Written and verbal presentation of results to team members and stakeholders 

• Reinforcing an environment of learning and progress with team members and others 

• Focus on accountability and innovation in leadership competency development 

• Duties, responsibilities and activities may change, or new ones may be assigned as needed 

• Machine learning engineers must maintain a commitment to ongoing learning in order to stay current with government missions and the ever-changing climate of data science and AI. This requires both ongoing education in relevant domains, such as physics, math, and/or computer science, as well as an understanding of the existing systems and future objectives of government missions. 

What You Need to be Successful 

Minimum Requirements for the Machine Learning Engineer- Senior Member of Technical Staff 

• Bachelors  degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering or related  technical field(s) 

• 5 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain 

• Strong proficiency in at least two different programming languages (e.g. Python, R, C/C++), and ML frameworks and familiarity with common libraries used for Data Science and Machine Learning, such as pandas, pytorch or JAX. 

• Experience with on and off-policy reinforcement learning algorithms such as Deep Q Learning, A3C, and PPO. 

• Working knowledge of fundamental graph theory and graph neural networks. 

• Hands on experience with container orchestration tooling (Docker, Kubernetes, etc.) 

• Experience with and understanding of software engineering concepts with an AI focus (MLOps/DevOps, ML Development Lifecycle, data structures, etc.) 

• Working knowledge of Unix/Linux operating systems 

• This position requires ability to obtain and maintain a security clearance, which is issued by the US government. U.S citizenship is required to obtain a security clearance. 

In addition to the above, the minimum requirements for the Machine Learning Engineer- Engineering Specialist : 

• 8 or more years of experience in Data Scientist or Machine Learning Engineer or AI/ML Researcher role in any domain 

• Demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration 

• Experience leading technical teams and in mentoring junior staff. 

• Familiarity with data pipelining and streaming technologies (Apache Kafka, temporal, etc.) 

How You Can Stand Out 

It would be impressive if you have one or more of these: 

• Advanced degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or related field(s) 

• Publications in reinforcement learning, graph theory, or a relevant AI/ML domain. 

• Experience in designing or managing enterprise-level ML platforms and production-grade ML models at scale 

• Familiarity with High Performance Computing hardware for ML (GPUs, TPUs), CUDA programming, and advanced ML optimization techniques and architectures 

• Demonstrated ability to exercise judgement and critical thinking in a scientific discipline 

• Experience implementing and guiding teams toward software development best practices 

• Experience in SQL, NoSQL, Cypher and other big data querying languages 

• Demonstrated contributions to open-source software repositories (github, kaggle, etc.) 

• Experience deploying ML models on cloud platforms (AWS, Azure, etc.) 

• Domain expertise relevant to one or more customer organization mission areas (USSF, NRO, etc.) 

• Active security clearance