Machine Learning / Computer Vision Engineer
$129,500 - $194,300 USD yearly
Originally posted 9 September 2026 by the employer — open 1 day.
About the role
You will develop algorithms optimized for heterogeneous, resource-constrained SoC platforms serving mobile, automotive, XR, IOT, and robotics customers.
What you'll do
- Research, design, and implement video processing and computer vision algorithms, including depth estimation, optical flow, video super-resolution, denoising, 3D reconstruction, visual odometry, and SLAM.
- Develop optimized model architectures and training strategies for deployment of deep learning at the edge, incorporating transformers, attention, VLA/VLM, and world models.
- Profile and optimize algorithm and model performance across memory, compute, power, and bandwidth constraints on mobile and embedded platforms.
- Collaborate with cross-functional teams (hardware, software, systems, and product) to ensure algorithms meet customer requirements.
- Own the training and development of new release models for important customer segments.
- Write clear and concise technical documentation, design specifications, and feature descriptions to guide internal teams and external partners.
What you'll need
- Bachelor's degree in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of relevant work experience; OR Master's degree in Computer or Electrical Engineering, Computer Science, or related field and 1+ year of relevant work experience; OR PhD in Computer or Electrical Engineering, Computer Science, or related field.
- Strong background in computer vision and video processing algorithms.
- Hands-on experience with modern deep learning architectures.
- Strong coding skills in Python (C/C++ is a plus) for production-quality development, optimization, and on-device deployment.
- Experience using ML/CV frameworks such as PyTorch, TensorFlow, ONNX, and OpenCV.
- Ability to work across algorithm, software, and hardware boundaries.
Nice to have
- 3 years of experience developing and implementing computer vision and video algorithms within system-level products.
- Comfortable using the latest AI coding assistants and productivity tools.
- Experience deploying AI algorithms on the edge (ExecuTorch, Jetpack, QNN, etc.) and understanding of associated tradeoffs and resource limitations (power, memory bandwidth, etc.).
- 3 years of experience working in a large, matrixed organization.
- Publication, patent, or external technical contribution experience.
Skills: computer vision, deep learning, optimized model architectures, deployment at the edge, algorithm and model performance, mobile and embedded platforms
This role has been open 0 days — well below the 63-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
508
|
Median days open
63 d
|
Median salary
$224k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Qualcomm | All employers we track in this specialty (508 roles · 79 employers) |
|---|---|---|
| Open roles in this specialty | 107 | 508 |
| Open roles in the wider Software, Firmware & Systems family | 713 | 5650 · 142 employers |
| Median days open | 98 d | 63 d (+35 d vs this employer) |
| Median salary (USD postings) | — | $224k |
Skills observed across this category: computer vision, deep learning, optimized model architectures, deployment at the edge, algorithm and model performance, mobile and embedded platforms
Who's hiring in this category
- Qualcomm (this employer) · 107 open roles · median 98 d
- NVIDIA · 88 open roles · median 60 d
- AMD · 44 open roles · median 63 d
- Micron Technology · 27 open roles · median 47 d
- Mobileye · 21 open roles · median 44 d
- NXP Semiconductors · 11 open roles · median 64 d
How we counted: 508 open AI/ML Hardware Engineering (AI ML Hardware) roles from 79 employers tracked in the SemiconductorJobs index, counted 10 Sept 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.