Associate Engineer, Machine Learning
About The Position
Silvus is seeking an Associate Engineer, Machine Learning who will report to the Research and Development (R&D) Director, Machine Learning on the Research and Development (R&D) team. The successful individual in this role focuses on supporting machine learning and data-driven techniques to improve the performance, efficiency, and adaptability of Silvus’ advanced MIMO radios and wireless networking systems. This role works closely under the guidance of experts in wireless communications, DSP, networking, and embedded systems to develop machine learning (ML) driven features that solve real-world problems in dynamic and challenging RF environments. This position is 100% onsite, Monday through Friday, at Silvus Technologies’ Engineering and R&D Office in Irvine, CA, near the vibrant Irvine Spectrum, with one day a week at Silvus HQ in West Los Angeles.
Requirements
- Bachelor of Science degree in Electrical Engineering, Computer Science, Computer Engineering, or related field plus a minimum of 0-2 years of experience in machine learning, with demonstrated application to real-world problems; no experience required with a graduate degree (M.S. or Ph.D.).
- Strong foundation in supervised and unsupervised learning and statistical modeling.
- Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
- Basic exposure to MATLAB or C/C++ for signal processing algorithm development.
- Must be a U.S. Citizen due to clients under U.S. government contracts.
- All employment is contingent upon the successful clearance of a background check and drug test.
Nice To Haves
- Master of Science degree in Electrical Engineering, Computer Science, or a related field.
- Demonstrated experience with radio frequency signal classification, anomaly detection, or spectrum monitoring.
- Proficiency in MATLAB or C/C++ for signal processing algorithm development.
- Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access).
- Familiarity with embedded ML, real-time systems, or deploying ML on edge devices.
- Background in adaptive modulation, beamforming, or cognitive radio techniques.
- Experience working with wireless standards such as 3GPP, IEEE 802.11/15, or military waveforms.
- Experience with GPU acceleration or model optimization for constrained environments.
- Excellent communication and collaboration skills.
Responsibilities
- Lead and assist in the research, design, and implement machine learning algorithms to enhance performance in wireless communication systems (e.g., link adaptation, interference mitigation, anomaly detection, spectrum sensing).
- Analyze real-world radio frequency (RF) datasets under senior guidance to extract insights and develop predictive models.
- Contribute to software prototypes and assist in integrating ML algorithms with Silvus’ radio firmware and networking stack.
- Collaborate with cross-functional teams to understand ML use cases and evaluate the impact of deployed models.
- Contribute to the design and maintenance of data pipelines and infrastructure for training, testing, and validating models.
- Participate in performance benchmarking and iterative improvement cycles.
- Stay current with the latest ML research on wireless and embedded systems.
- Make informed technical decisions regarding model development, testing strategies, and implementation approaches, escalating issues and recommendations as appropriate.
- Perform other related duties of which the above are representative.
Benefits
- Incentive Bonus Plans
- Medical, Dental, Vision benefits
- 401K with Company Match
- 10 Paid Holidays
- Generous Paid Time Off Packages
- Employee Stock Purchase Plan
- Paid Parental & Family Leave
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
