Machine Learning Engineer

Motorola Solutions•Los Angeles, CA

5d•$150,000 - $180,000•Onsite

About The Position

Would you like to join a talented group of people, doing challenging work, with the mission of “Keeping Our Heroes Connected”? You will join the Signals and Systems group where you will be developing machine learning solutions that enhance performance in wireless communication systems. Your work will directly impact our customers in the form of products and services that make use of signal processing technology. Unlike similar roles in the industry, the result of your work has the potential to impact the entire lifecycle of the workflows impacting people's lives in moments that matter.

Requirements

4+ years experience as a machine learning engineer
Expert knowledge in Python and an ML framework such as PyTorch or TensorFlow
Experience with RF signal processing and SDR for signals intelligence or electronic warfare
Strong foundation in supervised and unsupervised learning and statistical modeling
Strong mathematics background, particularly in linear algebra and probability
Strong written and oral communication skills
Bachelor degree with 4+ years experience as a machine learning engineer
2+ years of Python and PyTorch or TensorFlow experience
2+ years of experience with RF signal processing
Must be a U.S. citizen with the ability to obtain necessary security clearance as required by government contract.

Nice To Haves

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 Linux, DevOps (command line)
Experience with containerized infrastructure (Docker, Kubernetes)
Familiarity with regulated environments, such as sovereign clouds

Responsibilities

Manage inputs gathered from unusual sources, including captures from software defined radio (SDR) over a wide range of RF signals
Combine knowledge of signal processing, probability and statistics, machine learning, and modern methods of artificial intelligence to build large-scale and high-throughput systems handling vast quantities of data
Collaborate with UX designers, infrastructure engineers, and other research scientists to develop prototypes and integrate ML algorithms that work across a wide range of scales from resource-constrained edge compute to full-sized data centers
Stay current with the latest machine learning research for wireless and embedded systems, applying ingenuity and a deep understanding of the problems at hand