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Deep Learning Engineer Jobs in Fremont, CA (NOW HIRING)

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... Design, train, and optimize custom deep learning models that understand CAD workflows and generate ...

Matroid

Deep Learning Field Engineer

Palo Alto, CA · On-site

$150K - $300K/yr

We're looking for a Deep Learning Field Engineer to operate at the forefront of CV deployment in industry - building best-in-class CV systems that leverage deep learning techniques to solve a broad ...

Matroid

Deep Learning Field Engineer

Palo Alto, CA · Hybrid

$150K - $300K/yr

We're looking for a Deep Learning Field Engineer to operate at the forefront of CV deployment in industry - building best-in-class CV systems that leverage deep learning techniques to solve a broad ...

Matroid

Deep Learning Field Engineer

Palo Alto, CA · On-site

$150K - $300K/yr

We're looking for a Deep Learning Field Engineer to operate at the forefront of CV deployment in industry - building best-in-class CV systems that leverage deep learning techniques to solve a broad ...

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Showing results 21-40

All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in Fremont, CA

Deep Learning Engineer information

See Fremont, CA salary details

$45K

$137.3K

$226.9K

How much do deep learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for deep learning engineer in Fremont, CA is $137,304.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,400.00 and $179,500.00 per year, depending on experience, location, and employer.

What is a deep learning engineer?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

What skills and qualifications does a deep learning engineer need?

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What does a deep learning engineer do?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are popular job titles related to Deep Learning Engineer jobs in Fremont, CA? For Deep Learning Engineer jobs in Fremont, CA, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Fremont, CA look for? The top searched job categories for Deep Learning Engineer jobs in Fremont, CA are:
What cities near Fremont, CA are hiring for Deep Learning Engineer jobs? Cities near Fremont, CA with the most Deep Learning Engineer job openings:
Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Fremont, CA as of August 2026, with employment types broken down into 83% Full Time, and 17% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $137,304 per year, or $66 per hour.

Senior Deep Learning Framework Communications Engineer

NVIDIA

Santa Clara, CA • On-site

Full-time

Re-posted 20 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

Job Summary:
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks and improve AI compilers for large-scale workloads.
Responsibilities:
• Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
• Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
• Improve AI compilers to hide communications or perform automatic fusion.
• Conduct in-depth AI workload performance characterization on multi-GPU clusters.
• Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
• Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
• Influence the roadmap of communication libraries - NCCL & NVSHMEM.
• Collaborate with a very dynamic team across multiple time zones.
Qualifications:
Required:
• B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience
• Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
• Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)
• Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
• Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)
• Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
• Adaptability and passion to learn new areas and tools
• Flexibility to work and communicate effectively across different teams and timezones
Preferred:
• Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
• Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes
• Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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