Machine Learning Engineer

Join our Signals and Systems group as a Machine Learning Engineer, where you will develop machine learning solutions to enhance performance in wireless communication systems. Your work will directly impact our customers and the entire lifecycle of workflows that affect people's lives. You will manage inputs from various sources, combine knowledge of signal processing and machine learning, collaborate with UX designers and infrastructure engineers, and stay current with the latest research. Benefits include flexible work models, paid time off, health care benefits, and more.

• Développer des solutions d'apprentissage automatique pour améliorer les performances des systèmes de communication sans fil.
• Gérer les entrées provenant de sources inhabituelles, y compris les captures de radio définie par logiciel (SDR).
• Collaborer avec des concepteurs UX, des ingénieurs en infrastructure et d'autres scientifiques de la recherche pour développer des prototypes.

• If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team
• Strong foundation in supervised and unsupervised learning and statistical modeling
• Strong mathematics background, particularly in linear algebra and probability
• 4+ years experience as a machine learning engineer
• Experience with RF signal processing and SDR for signals intelligence or electronic warfare
• Strong written and oral communication skills
• Expert knowledge in Python and an ML framework such as PyTorch or TensorFlow
• AND 2+ years of Python and PyTorch or TensorFlow experience
• Must be a U.S. citizen with the ability to obtain necessary security clearance as required by government contract
• Bachelor degree with 4+ years experience as a machine learning engineer
• AND 2+ years of experience with RF signal processing
• Advanced degree in a quantitative field such as electrical and computer engineering, physics, mathematics or statistics
• Familiarity with relational and NoSQL databases
• Familiarity with cloud-based infrastructure: Azure and/or AWS
• Experience tracking projects with Jira, Azure DevOps or similar tooling
• Experience with containerized infrastructure (Docker, Kubernetes)
• Experience with Linux, DevOps (command line)
• Familiarity with regulated environments, such as sovereign clouds