Senior Deep Learning Engineer – Autonomous Vehicles
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$224k–$357k/yr
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Skills: Deep Learning, Distributed Systems, PyTorch, Python, C++
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San Francisco, California, United States · On-site
$163k–$236k/yr
Senior$26M raised
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San Francisco, California, United States · Remote Solely
$150k–$170k/yr
Senior+$413M raised
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Senior Embedded Systems Engineer (Quantum Computing)
Boulder, Colorado, United States · Hybrid
$131k–$175k/yr
Senior$438M raised
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$224k–$357k/yr
Full-time
bachelor degree, postgraduate degree
Equity, Benefits
Posted 3d ago
~40 hrs/week
Responsibilities
You will build and scale deep learning infrastructure libraries and frameworks to support large-scale training on multi-thousand GPU clusters. Additionally, you will collaborate with research and platform teams to optimize training pipelines, data loaders, and distributed training performance.
Requirements
Candidates must have a degree in Computer Science, Electrical/Computer Engineering, or a related field, along with 12+ years of experience in distributed systems. Proficiency in Python, C++, and deep learning frameworks like PyTorch is required, as well as strong knowledge of large-scale training and datacenter infrastructure.
Full job description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are in search of a Senior Deep Learning Systems Engineer to propel NVIDIA’s Autonomous Vehicles project forward. In this role, you will build and scale training libraries and infrastructure that make end-to-end autonomous driving models possible. By enabling training on thousands of GPUs and massive datasets, you will accelerate iteration speed and improve safety, working closely with research and platform teams across NVIDIA.
What you’ll be doing:
Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.
What we need to see:
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.
12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.
Extensive knowledge in deep learning frameworks (PyTorch is preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.
Proficiency in Python and C++, with experience writing production-grade libraries, orchestration layers, and automation tools.
Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.
Ways to stand out from the crowd:
Shown experience scaling large GPU training clusters with >1,000 GPUs.
Contributions to open-source ML systems libraries (e.g., PyTorch, NCCL, FSDP, schedulers, storage clients).
Expertise in fault resilience and high availability, including elastic training and large-scale observability.
Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.
Familiarity with reinforcement learning (RL) at scale, particularly in the context of simulation-heavy workloads.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning
Related keywords
Deep LearningAutonomous VehiclesGPUDistributed SystemsPyTorchDDPFSDPNCCLRoCEInfiniBandLustreSlurmKubernetesPythonC++Infrastructure Engineering
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
Offices: 2701 San Tomas Expressway, Santa Clara, CA 95050, US · No. 8, Ji Hu Rd., Taipei City, Taipei City 114, TW · Nanakramguda, Serilingampally Mandal, Plot # 6A&B, IT Park Layout, RR District, Hyderabad, Telangana 500046, IN · No. 127 Andheri Kurla Road, CNB Square, Mumbai, Village Chakala, Andheri East 400 093, IN · Survey No. 144/145, Samrat Ashok Path, Off Airport Road, Pune, Yerwada 411 006, IN
Based on 335 listings with disclosed salaries, most technology jobs in Boulder, CO pay between $83k–$219k per year. Individual offers vary with seniority, company size, and specialization.
How many Technology jobs are open in Boulder, CO right now?
There are currently 366 open technology positions in Boulder, CO listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Technology roles in Boulder, CO?
Companies currently hiring include Google, SciTec, Northrop Grumman, Northrop Grumman Mission Systems, Inc., The GEO Group, Inc., among others. Browse the listings above to see every active employer.
Are there remote or hybrid Technology jobs in Boulder, CO?
Yes — 122 of the 366 open technology positions offer remote or hybrid work (33 remote, 89 hybrid).
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Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.