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Job description
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.
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