Data Science and AI Engineer

The Aerospace Corporation•Chantilly, VA

1d•$0 - $480•Onsite

About The Position

The Aerospace Corporation is the trusted partner to the nation’s space programs, solving the hardest problems and providing unmatched technical expertise. As the operator of a federally funded research and development center (FFRDC), we are broadly engaged across all aspects of space— delivering innovative solutions that span satellite, launch, ground, and cyber systems for defense, civil and commercial customers. When you join our team, you’ll be part of a special collection of problem solvers, thought leaders, and innovators. Join us and take your place in space. Job Summary We are seeking a highly skilled Data Science & AI Engineer (IT Casual – Specialist IV) to join our team. In this role, you will be responsible for the end-to-end lifecycle of AI products, from conducting exploratory data analysis and developing machine learning models to implementing, testing, and deploying these solutions into production environments. The selected candidate will be required to work part-time on-site at our facility in Chantilly, VA. This is a casual part-time role.

Requirements

Master’s or Ph.D. degree in Computer Science, Data Science, Mathematics, Engineering or related field is required
A minimum of (15) years of experience, working across multiple industries, and thrives on translating complex data challenges into actionable insights and building self-learning applications that drive business impact is required
Expert-level proficiency in Python and familiarity with languages like Scala or Java for production systems
Strong hands-on experience with TensorFlow, PyTorch, or Scikit-learn
Proficient in SQL and NoSQL databases, as well as data manipulation libraries (Pandas, NumPy)
Experience deploying models on cloud platforms (AWS SageMaker, Azure ML, or GCP) and nice to have experience with containerization tools (Docker, Kubernetes)
Familiarity with vector databases (e.g., Pinecone, Milvus), LangChain, and RAG (Retrieval-Augmented Generation) techniques
Strong analytical thinking, problem-solving, and the ability to explain technical concepts to a diverse audience
Casual employment is normally for fewer than 20 hours a week, usually non-continuous, irregular, and infrequent

Nice To Haves

Experience with Agentic AI frameworks (e.g., LangGraph, AutoGen) is preferred
Proven experience in Natural Language Processing (NLP) or Computer Vision (CV)
Experience with Data tools (Apache Spark, Kafka) is preferred

Responsibilities

Design, build, and train advanced machine learning (ML), deep learning (DL), and Generative AI (GenAI) models (including LLMs) to address complex business challenges
Convert data science prototypes into production-ready services, managing model versioning, monitoring, and continuous training (CI/CD)
Build and maintain scalable data pipelines for ingestion and processing of structured and unstructured data, ensuring high-quality data for training
Transform machine learning models into robust APIs for integration with software products, such as recommendation engines, chatbots, or automated assistants
Perform rigorous statistical analysis, A/B testing, and model tuning to ensure high performance, accuracy, and efficiency
Work closely with cross-functional teams (App-Dev\Product, Engineering, Enterprise Services Business Units) to define AI strategies, translate requirements into technical specifications, and communicate findings to non-technical stakeholders

Benefits

Comprehensive health care and wellness plans
Paid holidays, sick time, and vacation
Standard and alternate work schedules, including telework options
401(k) Plan — Employees receive a total company-paid benefit of 8%, 10%, or 12% of eligible compensation based on years of service and matching contributions; employees are immediately eligible and vested in the plan upon hire
Flexible spending accounts
Variable pay program for exceptional contributions
Relocation assistance
Professional growth and development programs to help advance your career
Education assistance programs
An inclusive work environment built on teamwork, flexibility, and respect