Applied Machine Learning Engineer
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, applying advanced compute hardware, and implementing MLOps and Trusted AI practices. The role supports national security, civil, and commercial space customers and contributes to enterprise capabilities, workforce development, and strategic priorities. It is a full-time, 100% onsite position based in Chantilly, Virginia; El Segundo, California; or Colorado Springs, Colorado. The role offers opportunities to work with multidisciplinary teams on AI and data-enabled tools across the space enterprise. Machine Learning Engineers are expected to keep learning about relevant domains, existing systems, and government mission objectives as data science and AI evolve. The position may involve changing or newly assigned duties and responsibilities. The posting describes requirements for two experience levels: Senior Member of Technical Staff requires at least five years of relevant experience, while Engineering Specialist requires at least eight years and additional enterprise-scale AI/ML architecture and MLOps experience. The position requires the ability to obtain and maintain a U.S. government security clearance; U.S. citizenship is required to obtain one.
Requirements
- Bachelor’s or master’s degree in computer science, computer information systems, electrical or computer engineering, or a related technical field.
- For Senior Member of Technical Staff: at least five years of experience as a data scientist, machine learning engineer, or AI/ML researcher 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 focused on 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 Engineering Specialist: at least eight years of experience as a data scientist, machine learning engineer, or AI/ML researcher in any domain.
- For Engineering Specialist: demonstrated experience architecting, designing, or implementing enterprise-scale AI/ML solutions with multiple tenants and cloud integration.
- For Engineering Specialist: 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, or 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 customer mission areas such as USSF or NRO.
- Active security clearance.
Responsibilities
- Evaluate technologies for use in scalable, resilient, mission-critical production applications.
- 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 written and verbal form to team members and stakeholders.
- Contribute to a learning- and progress-oriented environment.
- Apply accountability and innovation in leadership competency development.
- Maintain ongoing learning in relevant technical domains and government mission areas.
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
