Description
Description
A trusted leader in cloud, digital engineering, data, and Artificial Intelligence, the nation looks to SAIC to integrate emerging technology to modernize critical missions and enable its national imperatives. To address the growing demands within the Department of Defense, SAIC is seeking a highly skilled and dynamic Machine Learning Engineer to support Data and AI Infrastructure Management for our Digital and AI Team as we embark on a large initiative to lead the design and operate integrated Enterprise IT solutions that deliver AI-enabled capabilities and enable data-driven decision making to missions across the Department, Services, and Combatant Commands.
The Ideal candidate will be adept at managing customer relationships, driving operational excellence, and fostering continuous improvement across all service areas.
Core Responsibilities
- Develops, researches, and applies analytic models, including machine learning and deep learning, to datasets in a variety of domains, including computer vision, natural language processing, or time series analysis.
- Experience working with GPU compute with leading libraries such as TensorFlow, Keras, and PyTorch.
- Experience or working knowledge of data engineering concepts.
- Works in cross-functional teams with data at all stages of the analysis lifecycle to derive actionable insight.
- Translates mission needs into an end-to-end analytical approach to achieve results.
- May perform the pre-analytics areas of data collection and understanding, data cleansing and integration, and data storage and retrieval.
- Determines the appropriate analytics based on the data and the desired outcomes.
- Interprets the validity of results and communicates the meaning of those results.
- Identify, design, build, test, and provide AI/ML Model-as-a-Service support.
- Deliver foundational-enterprise data products and AI/ML workflows.
- Provide technical expertise and development support for AI/ML tasks within the Advana platform.
- Design, build, operate, and maintain data and AI model connections for the Advana System.
- Support the establishment of automated data connections for Government-directed use cases.
- Maintain existing standard data connection methods, both inbound and outbound.
- Develop and maintain a training and certification program for data connection engineers.
- Plan and conduct enterprise data operations for the Advana System across all CSP/Security Environments.
- Deliver automated data movement capabilities, alerting, and data drift detection throughout the data lifecycle.
- Manage automated solutions for data ingress and egress using enterprise APIs.
Qualifications
- Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD or JD and zero (0) years or more related experience.
- Security+ Certification
- U.S. citizenship and a Secret security clearance is required.
Preferred Qualifications:
- Experience in enterprise data operations and AI/ML model deployment.
- Proficiency in managing data connections, APIs, and cross-domain data federation.
- Strong understanding of data lifecycle management, data pipeline development, and automated data movement.
- Knowledge of AI/ML operations, including model integration, deployment, and federated AI development.
- Excellent problem-solving skills and ability to proactively address data connection issues.
- Strong communication and collaboration skills to facilitate technical exchange meetings and data sharing agreements.
- AWS AI Practitioner Certification
- Python Certification
- Data+ Certification
Join SAIC: Be a part of a team that's passionate about the power of AI to transform the public sector.
Apply Now: Interested candidates with a drive for innovation are encouraged to apply. Share your passion, expertise, and leadership by joining our team.
SAIC accepts applications on an ongoing basis and there is no deadline.
Covid Policy: SAIC does not require COVID-19 vaccinations or boosters. Customer site vaccination requirements must be followed when work is performed at a customer site.
Apply on company website