Applied Machine Learning Engineer
About The Position
The Aerospace Corporation is seeking a creative and enthusiastic Machine Learning Engineer to join a collaborative team of engineers, data scientists, and programmers developing AI- and data-enabled tools across the space enterprise. The role supports National Security Space, civil, and commercial customers and contributes to enterprise capabilities, workforce development, and strategic focus areas. The position is part of the Machine Learning Engineering section, which translates AI research into robust, scalable, production-ready machine learning solutions. The team optimizes and scales ML models, designs ML software architectures, applies advances in compute hardware, and implements MLOps and Trusted AI practices. Engineers collaborate across disciplines and organizational boundaries, conducting research and experiments, developing prototypes, and delivering features and products. This is a full-time, 100% onsite position based in Chantilly, Virginia; El Segundo, California; or Colorado Springs, Colorado. The position requires the ability to obtain and maintain a U.S. government security clearance, which requires U.S. citizenship. The posting describes minimum qualifications for both the Senior Member of Technical Staff and Engineering Specialist levels.
Requirements
- Bachelor’s or master’s degree in Computer Science, Computer Information Systems, Electrical Engineering, 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.
- 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.
- 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 applied to AI, including MLOps/DevOps, the ML development lifecycle, and data structures.
- Working knowledge of Unix/Linux operating systems.
- 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.
- Ability to obtain and maintain a U.S. government security clearance; U.S. citizenship is required to obtain a clearance.
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 judgment and critical thinking in a scientific discipline.
- Experience implementing software development best practices and guiding teams toward them.
- Experience with SQL, NoSQL, Cypher, or other big data querying languages.
- Experience with big data frameworks such as Hadoop, Spark, or Flink.
- Familiarity with data pipeline 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 customer mission areas such as USSF or NRO.
- Active security clearance.
Responsibilities
- Evaluate technologies for use in 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 to team members and stakeholders in writing and verbally.
- Promote learning and progress among team members and others.
- Apply data science and AI knowledge across the space enterprise, Aerospace enterprise capabilities, workforce development, and strategic focus areas.
- Maintain ongoing learning in relevant technical domains and about government mission systems and objectives.
- Support customers across national security, civil, and commercial domains.
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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
