AI/ML Engineer working on a national security team to train, test, deploy, monitor, and maintain models that learn from data using best-fit ML algorithms and technologies.
Compensation
The projected compensation range for this position is $77,600.00 to $176,000.00 (annualized USD).
Responsibilities
Train, test, deploy, monitor, and maintain models that learn from data
Contribute to the direction of mission-critical solutions by applying best-fit ML algorithms and technologies
Collaborate with data engineers, software developers, data scientists, and mission stakeholders
Apply AI/ML solutions to solve cutting edge problems
Triage large datasets
Requirements
Bachelor's degree in a STEM field
Nice to have: communicating technical solutions to non-technical stakeholders
Nice to have: deploying generative AI systems into production environments
Nice to have: Experience working in the Intelligence Community
Design, develop, and deploy large-scale machine learning models and AI pipelines across Meta's product surfaces, including ranking, recommendation, and generative AI systems.
Locations (5)
Los Angeles, California, United States
Redmond, Washington, United States
Burlingame, California, United States
New York, New York, United States
Seattle, Washington, United States
Responsibilities
Design, develop, and deploy large-scale machine learning models and AI pipelines across Meta's product surfaces, including ranking, recommendation, and generative AI systems
Own the end-to-end technical design of AI/ML systems, evaluating architectural trade-offs and selecting appropriate modeling approaches, training strategies, and inference frameworks
Instrument and profile ML training and serving pipelines to identify performance bottlenecks, reduce latency, and optimize compute efficiency at scale
Establish and maintain model evaluation frameworks, including offline metrics, online experimentation, and monitoring to ensure production model quality and reliability
Collaborate with product managers, data scientists, and research scientists to translate product requirements into ML problem formulations and deliver measurable improvements to key metrics
Requirements
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
