Applied Machine Learning Engineer

The Aerospace Corporation • Chantilly, VA

18h • Onsite

About The Position

The Aerospace Corporation is seeking a Machine Learning Engineer for its Machine Learning Engineering section within the Information Systems and Cyber Division. The section translates cutting-edge AI research into robust, scalable, production-ready machine learning solutions by optimizing and scaling models, designing ML software architectures, using advanced compute hardware, and implementing MLOps and Trusted AI practices. The role supports customers across national security, civil, and commercial space and related domains, contributing data science and AI expertise across the enterprise. The position is full-time and based in Chantilly, Virginia, with 100% onsite work. The posting describes minimum qualifications for Senior Member of Technical Staff and additional qualifications for Engineering Specialist. The role requires the ability to obtain and maintain a U.S. government security clearance, for which U.S. citizenship is required. Ongoing learning is expected to maintain current knowledge of government missions and advances in data science and AI.

Requirements

• Bachelor’s or master’s degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or a related technical field.
• At least 5 years of experience in a Data Scientist, Machine Learning Engineer, or AI/ML Researcher role in any domain for the Senior Member of Technical Staff level.
• Strong proficiency in at least two programming languages, such as Python, R, or C/C++, and familiarity with machine learning and deep learning libraries in Python.
• Hands-on experience with container orchestration tools such as Docker or Kubernetes.
• Experience with and understanding of software engineering concepts relevant to AI, including MLOps/DevOps, the ML development lifecycle, and data structures.
• Working knowledge of Unix/Linux operating systems.
• Ability to obtain and maintain a U.S. government security clearance; U.S. citizenship is required to obtain a clearance.
• For the Engineering Specialist level: at least 8 years of experience in a Data Scientist, Machine Learning Engineer, or AI/ML Researcher role in any domain.
• For the Engineering Specialist level: demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration.
• For the Engineering Specialist level: hands-on experience with MLOps and data engineering tools such as MLFlow, Kubeflow, Neptune, Airflow, or DVC.

Nice To Haves

• Advanced degree in Computer Science, Computer Information Systems, Electrical or Computer Engineering, or a related field.
• Experience designing or managing enterprise-level ML platforms and production-grade ML models at scale.
• Familiarity with high-performance computing hardware for ML, including GPUs and TPUs, CUDA programming, and advanced ML optimization techniques and architectures.
• Demonstrated ability to exercise judgment and critical thinking in a scientific discipline.
• Experience implementing and guiding teams toward software development best practices.
• Experience with SQL, NoSQL, Cypher, and other big data querying languages.
• Experience with big data frameworks such as Hadoop, Spark, or Flink.
• Familiarity with data pipelining and streaming technologies such as Apache Kafka or Temporal.
• Demonstrated contributions to open-source software repositories, such as GitHub or Kaggle.
• Experience deploying ML models on cloud platforms such as AWS or Azure.
• Domain expertise relevant to one or more customer mission areas, such as USSF or NRO.
• Active security clearance.

Responsibilities

• Evaluate technologies for scalable, resilient, mission-critical applications in production environments.
• Coordinate the development and execution of AI/ML experiments.
• Coordinate the development of proof-of-concept infrastructure configurations and software prototypes.
• Collaborate with small, innovative teams to deliver features and products.
• Present results in writing and verbally to team members and stakeholders.
• Contribute to a learning- and progress-oriented environment with team members and others.
• Apply accountability and innovation in leadership competency development.
• Maintain ongoing learning in relevant domains and develop understanding of government mission systems and objectives.

Benefits

• Comprehensive health care and wellness plans.
• Paid holidays, sick time, and vacation.
• Standard and alternate work schedules, including telework options.
• 401(k) plan with company-paid contributions of 8%, 10%, or 12% of eligible compensation based on years of service, plus matching contributions; employees are immediately eligible and vested upon hire.
• Flexible spending accounts.
• Variable pay program for exceptional contributions.
• Relocation assistance.
• Professional growth and development programs.
• Education assistance programs.
• Inclusive work environment built on teamwork, flexibility, and respect.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior