Senior Machine Learning Engineer - San Diego, CA, United States
$140,000 - $178,000 USD yearly
Originally posted 26 August 2026 by the employer.
Work on machine learning models for automotive radar sensing products.
About the role
The Senior Machine Learning Engineer works on real-world challenges where machine learning directly impacts the performance of automotive radar sensing products.
What you'll do
- Design and develop machine learning models for radar signal processing.
- Develop end-to-end ML pipelines, including data preprocessing, feature extraction, model training, validation, and performance optimization for radar data.
- Analyze and model raw and processed radar data (e.g., time-domain, frequency-domain, range–Doppler, range–angle representations).
- Evaluate and implement ML and deep learning techniques for radar-based detection, classification, and tracking.
- Optimize models for real-time and embedded deployment, considering constraints such as latency, memory, and power.
- Support product development through algorithm validation, performance benchmarking, and documentation.
What you'll need
- Master’s or PhD in Applied Mathematics, Statistics, Electrical Engineering, Computer Science, or a related field.
- 3+ years’ research experience in developing machine learning models and applied statistics.
- Strong understanding of radar fundamentals and signal processing concepts.
- Proven experience applying ML/DL techniques (e.g., CNNs, RNNs, Transformers, classical ML) to radar or similar sensing modalities.
- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow; experience with data analysis tools (NumPy, SciPy, pandas).
- Ability to train, build, deploy, and manage machine learning models for radar applications such as Google Colab, AWS, or similar platforms.
- Strong statistical and mathematical skills to act as the in-house mathematician/statistician.
Nice to have
- Experience applying machine learning to radar, perception, robotics, or autonomous systems.
- Deep understanding of signal processing and sensor data analysis.
- Proven track record of designing ML models that deliver measurable product impact.
- Experience with time domain samples, data augmentation and field testing.
- Publications, patents, or noteworthy technical contributions in ML or sensing technologies.
Skills: machine learning models, radar signal processing, ML pipelines, PyTorch, TensorFlow
This role has been open 50 days — below the 51-day median for Software Engineering Semiconductor roles.
Software Engineering Semiconductor · AI ML Hardware
|
Open roles in category
164
|
Median days open
51 d
|
Median salary
$191k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | pSemi | All employers we track in this specialty (164 roles · 44 employers) |
|---|---|---|
| Open roles in this specialty | 1 | 164 |
| Open roles in the wider Software, Firmware & Systems family | 4 | 6127 · 145 employers |
| Median days open | 50 d | 51 d (−1 d vs this employer) |
| Median salary (USD postings) | — | $191k |
Skills observed across this category: machine learning models, radar signal processing, ML pipelines, PyTorch, TensorFlow
Who's hiring in this category
- Micron Technology · 28 open roles · median 34 d
- NVIDIA · 26 open roles · median 189 d
- Qualcomm · 22 open roles · median 189 d
- Infineon Technologies · 10 open roles · median 43 d
- AMD · 8 open roles · median 65 d
- Applied Materials · 4 open roles · median 85 d
How we counted: 164 open Software Engineering Semiconductor (AI ML Hardware) roles from 44 employers tracked in the SemiconductorJobs index, counted 15 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.