Manager, Deep Learning – Autonomous Vehicles and Robotics
Originally posted 30 October 2026 by the employer. Relisted by the employer on 31 October 2026.
About the role
Lead a team of engineers in the Tegra Solutions Engineering organization delivering deep learning solutions for autonomous vehicles and robotics on edge hardware. The team focuses on model architectures, compiler technology, and embedded deployment across NVIDIA DRIVE and Jetson platforms.
What you'll do
- Lead and develop an engineering team delivering inference optimization and model enablement solutions for automotive and robotics customers.
- Drive technical engagements with OEM partners, managing scoping, resource allocation, and delivery of production-quality solutions.
- Set technical direction for optimizing and deploying modern architectures—such as transformers, vision-language models, and state space models—on GPU and SOC platforms.
- Partner with compiler, runtime, and hardware teams to align customer workload patterns with platform capabilities and roadmap priorities.
- Coordinate with research and internal deep learning teams to transition new techniques into production environments.
- Represent NVIDIA externally at partner reviews, conferences, and industry forums.
What you'll need
- Master's degree or equivalent experience in Computer Science, Electrical Engineering, or a related field.
- 8+ years of overall experience with at least 5 years in deep learning model optimization, inference engineering, or neural network compilation.
- 4+ years of team leadership experience.
- Proven ability to manage concurrent technical customer engagements and deliver under production constraints.
- Strong knowledge of current deep learning architectures and inference optimization toolchains such as TensorRT or equivalent.
Skills: Deep Learning Engineering, autonomous vehicles, robotics, model architectures, compiler technology, inference optimization
More semiconductor jobs: NVIDIA jobs · AI chip design jobs · California jobs
This role has been open 191 days — well above the 92-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
478
|
Median days open
92 d
|
Category median salary (all employers)
$236k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | NVIDIA | All employers we track in this specialty (478 roles · 77 employers) |
|---|---|---|
| Open roles in this specialty | 102 | 478 |
| Open roles in the wider Software, Firmware & Systems family | 1117 | 6360 · 144 employers |
| Median days open | 74 d | 92 d (−18 d vs this employer) |
| Median salary (USD postings) | — | $236k |
Skills observed across this category: Deep Learning Engineering, autonomous vehicles, robotics, model architectures, compiler technology, inference optimization
Who's hiring in this category
- Qualcomm · 95 open roles · median 122 d
- NVIDIA (this employer) · 88 open roles · median 66 d
- AMD · 32 open roles · median 114 d
- Mobileye · 19 open roles · median 89 d
- Micron Technology · 18 open roles · median 74 d
- Analog Devices · 15 open roles · median 49 d
How we counted: 478 open AI/ML Hardware Engineering (AI ML Hardware) roles from 77 employers tracked in the SemiconductorJobs index, counted 31 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.