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Deep Learning Developer Jobs in California (NOW HIRING)

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 ...

Skydio

Senior Autonomy Engineer - Deep Learning

San Mateo, CA · On-site

$63 - $81.25/hr

Required : • Demonstrated hands-on experience creating and deploying deep learning models • Experience curating synthetic and real-world image datasets • Solid software engineering foundation ...

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Deep Learning Developer information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
What cities in California are hiring for Deep Learning Developer jobs? Cities in California with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Senior Deep Learning Compiler Engineer

Senior Deep Learning Compiler Engineer

Nvidia Corporation

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 19 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

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 looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.
What you'll be doing:
  • Analyzing deep learning networks and developing compiler optimization algorithms.
  • Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.
  • Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.

What we need to see:
  • Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
  • 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
  • Ability to work independently, define project goals and scope, and lead your own development efforts.
  • Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
  • Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.

Ways to stand out from the crowd:
  • Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.
  • Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.
  • Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.
  • GPU kernel generation with high performance and fast build time.
  • A track record of success in mentoring junior engineers and interns is a bonus.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 4, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.
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What Nvidia employees say

Hours and flexibility

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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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