Artificial Intelligence/Machine Learning Engineer (AI/ML)
About The Position
SAIC is seeking an AI/ML Engineer to join our team conducting a wide variety of analyses in support of Government satellite programs in Earth orbits. Areas of work may include: Recognizing different types of satellites based on observations of them using optical and radar sensors, Scheduling space surveillance sensors to collaboratively find, recognize and track maneuvering satellites, Deciding what activities satellites should undertake. Satellite designers and operations planners will leverage your analyses to inform critical decisions. As part of an agile team including experts in astrodynamics, sensors and AI/ML you will collaboratively simulate operations concepts at-scale with support from our cloud computing and supercomputing specialists. You can expect regular opportunities to meet with and optionally present findings to local senior government customers.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Applied Math, or a related technical field plus two years of experience, OR Master’s degree plus zero years of experience, OR PhD plus zero years of experience
- Experience in Astrodynamics
- Programming experience in Python, C++, MATLAB, or similar
- Minimum of TS/SCI clearance
- Must have current or be able to pass polygraph test
Responsibilities
- Use programming languages such as Python, C++, or others to leverage existing analysis tools and develop new ones
- Conduct independent trade studies and technical assessments
- Review and validate algorithms and results provided by external teams
- Develop and optionally present actionable technical briefings
- Conduct Exploratory Data Analysis (EDA) to identify patterns for feature engineering
- Design, develop, and evaluate machine learning algorithms, including supervised, unsupervised, and reinforcement learning
- Build, train, and tune predictive models using state-of-the-art frameworks and tools
- Collaborate with cross-functional teams to identify challenges, define problems, and translate them into actionable AI/ML solutions
- Implement and optimize algorithms for tasks such as anomaly detection, prediction, classification, optimization, clustering, and natural language processing
- Deploy machine learning models into production environments and establish pipelines for scalability and monitoring
- Analyze model performance and identify opportunities for improvement by leveraging testing strategies and tuning hyperparameters
Benefits
- 401(k) match
- Discounted employee stock purchase plan
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
