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Nvidia Machine Learning Jobs (NOW HIRING)

FieldAI

3D Machine Learning Engineer

Irvine, CA

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

Nvidia

Solutions Architect, AI and ML

Seattle, WA

$71.75 - $94.50/hr

... in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and ...

Nvidia

Senior AI Compiler Engineer

Austin, TX · On-site

$103K - $142K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

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Nvidia Machine Learning information

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$25.5K

$42.6K

$88K

How much do nvidia machine learning jobs pay per year?

As of Jul 1, 2026, the average yearly pay for nvidia machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

What is a Nvidia Machine Learning job?

A Nvidia Machine Learning job involves developing and optimizing AI models, deep learning frameworks, and GPU-accelerated applications. Engineers in this role work on cutting-edge research, building scalable ML solutions, and improving performance on Nvidia hardware like GPUs and AI accelerators. They collaborate with software and hardware teams to enhance AI capabilities across industries such as gaming, healthcare, and autonomous systems. Strong coding skills in Python, C++, and experience with ML frameworks like TensorFlow or PyTorch are often required.

What are the key skills and qualifications needed to thrive in the Nvidia Machine Learning position, and why are they important?

To thrive in an Nvidia Machine Learning role, a deep understanding of machine learning algorithms, proficiency in programming languages like Python or C++, and a solid background in mathematics or computer science are essential. Experience with Nvidia's CUDA, TensorRT, cuDNN, and familiarity with modern deep learning frameworks such as TensorFlow or PyTorch are highly valued, as are relevant certifications in AI or data science. Strong problem-solving skills, teamwork, and effective communication distinguish top candidates in collaborative, fast-paced environments. These skills are crucial for developing and optimizing AI solutions that leverage Nvidia’s advanced hardware and software platforms.

Does NVIDIA do machine learning?

Nvidia offers extensive tools and platforms for machine learning, including GPUs optimized for training and deploying models. Many machine learning engineers and researchers use Nvidia hardware and software frameworks like CUDA and cuDNN to accelerate AI development. The company also provides AI-focused products and solutions for various industries.

Is it hard to get hired at NVIDIA?

Getting hired for a machine learning role at NVIDIA can be competitive due to the company's focus on advanced technology and innovation. Candidates typically need strong technical skills in deep learning, programming, and relevant experience, along with a solid educational background. The hiring process often involves multiple interviews and technical assessments to evaluate expertise and problem-solving abilities.

What are some common challenges faced by professionals in Nvidia Machine Learning roles?

One common challenge in Nvidia Machine Learning roles is optimizing models to fully leverage GPU architectures for both performance and efficiency, which requires continuous learning as the technology rapidly evolves. Team members often work on complex, large-scale projects that demand close collaboration across software, hardware, and research divisions. Navigating the fast pace of innovation and contributing effectively to cross-functional teams is essential for success. However, these challenges also make the role exciting and offer excellent opportunities for professional growth and hands-on experience with state-of-the-art AI solutions.

Is ML a high paying job?

Machine Learning roles, including positions like Nvidia Machine Learning engineers, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and company, but these jobs tend to offer above-average compensation compared to many other tech roles.
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Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 40% Full Time, and 58% Part Time. Highlights an 88% Physical, 6% Hybrid, and 6% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

3D Machine Learning Engineer

FieldAI

Irvine, CA

Other

Posted 20 days ago

Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
What You'll Do
  • Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene understanding.
  • Train, optimize, and deploy deep learning models using PyTorch, TensorFlow, or equivalent frameworks on cloud platforms such as AWS (e.g., SageMaker, EC2).
  • Collaborate with software and systems engineers to integrate models into production environments and continuously improve inference pipelines.
  • Analyze diverse sensor inputs, including RGBD imagery, LiDAR point clouds, 360 photos, audio, and Building Information Models (BIM).
  • Work closely with the labeling and data operations teams to define robust data annotation strategies and ensure high model performance and generalization.
What You Have
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Robotics, or a related technical field.
  • 2+ years of hands-on industry experience developing and deploying machine learning systems for 3D point clouds, perception, or spatial understanding tasks.
  • Strong background in 3D machine learning, with experience in deep learning for point clouds, multi-view fusion, or geometric learning.
  • Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.
  • Familiarity with OpenCV and PCL (Point Cloud Library) for classical computer vision and 3D data preprocessing.
  • Experience training, evaluating, and deploying ML models using cloud infrastructure (e.g., AWS, SageMaker) and containerized workflows.
  • Solid understanding of the end-to-end ML lifecycle, including experiment tracking, reproducibility, model versioning, and optimization for production.
  • Proven ability to work in fast-paced, interdisciplinary teams across software, ML, and product teams.
The Extras That Set You Apart
  • Experience working with BIM data, digital twins, or construction-related sensor data.
  • Background in geometric deep learning, 3D mesh analysis, GIS systems, or structured scene representations.
  • Familiar with MLOps pipelines using Ray, SageMaker, MLflow, or Kubeflow.
  • Strong foundation in geometric computer vision, robotics, or algorithmic 3D reasoning.
  • Exposure to graph neural networks, geodesic computations, or neural implicit representations (e.g., NeRF, Occupancy Networks).
  • Deep experience with point cloud and graph learning frameworks such as Open3D-ML, Torch-Points3D, PyG, or MMDetection3D.
  • Experience building custom modules for SparseConvNet or 3D transformers.
Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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