Machine Learning Engineer / Wireless Systems / Hybrid Los Angeles

Job Description

This is a full-time opportunity for a Machine Learning Engineer based in Los Angeles, CA (hybrid schedule, 3 days onsite). Our client is a specialized engineering firm focused on developing next-generation wireless systems. Their work centers around building intelligent, resilient communication technologies designed to perform reliably in unpredictable and demanding environments.

This is a unique opportunity to apply machine learning to real-world wireless communication problems. You’ll work alongside experts in signal processing, embedded systems, and networking to develop ML-driven features that enhance performance, efficiency, and adaptability. If you're passionate about solving complex technical challenges and want to work on systems that truly matter, this role offers a chance to make a tangible impact while growing your skills in a highly specialized domain.

Required Skills & Experience
· M.S. or Ph.D. in Electrical Engineering, Computer Science, or related field
· 3+ years of experience in machine learning
· Strong foundation in supervised/unsupervised learning, signal processing, and statistical modeling
· Proficiency with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
· Familiarity with wireless communication systems (e.g., MIMO, OFDM, SDRs)
· Experience with MATLAB or C/C++ for signal processing development

Desired Skills & Experience
· Experience integrating ML models into embedded or real-time systems
· Background in Radio Frequency data analysis or spectrum sensing
· Experience building data pipelines for model training and validation

What You Will Be Doing

Tech Breakdown
· Machine Learning & Data Analysis
· Signal Processing & Wireless Systems
· Software Prototyping & Integration

Daily Responsibilities
· 70% Hands-On Development
· 10% Research & Algorithm Design
· 20% Cross-functional Collaboration

The Offer
· Bonus eligible

You will receive the following benefits:
· Medical, Dental, and Vision Insurance
· Vacation Time

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.