About the role
L3Harris is dedicated to recruiting and developing high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers’ mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do.
L3Harris is the Trusted Disruptor in defense tech. With customers’ mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security.
Job Location: Melbourne, FL or Rochester, NY
Job Schedule: 9/80: Employees work 9 out of every 14 days – totaling 80 hours worked, and have every other Friday off
Job Description
Work closely with current team members to support development of machine learning solutions using data-driven models
Contribute to the improvement of MLOps and data pipelines with the current team
Work with multi-domain datasets and phenomenologies to develop effective data plans
Perform data curation and exploratory data analysis
Support proper regression testing, validation, and documentation of ML models
Identify relevant pre-trained models and collaborate with team to integrate into solution pipelines
Identify state-of-the-art (SotA) foundation models and advocate for use in larger AI solutions
Implement, maintain, and optimize containerization for seamless deployment, scaling of AI / ML workloads, and sharing with other teams for easy reproduction
Qualifications
Pursuing a Master’s Degree in Artificial Intelligence, Computer Engineering, Computer Science, Mathematics, or related technical degree at an accredited university.
Preferred Additional Skills
Experience with Differentiable Programming libraries (e.g., PyTorch, TensorFlow)
Experience with Database Manipulation libraries (e.g., SQL, NoSQL, Pandas, PySpark)
Experience with Python and building Virtual Environments (e.g., Conda, UV, Docker)
Experience developing models using classical and SotA…
