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Deep Learning Engineer Jobs in California (NOW HIRING)

Hayden AI

Deep Learning Engineer

San Francisco, CA · On-site

$161K - $175K/yr

About the Role As a Deep Learning Engineer at Hayden, you will make key contributions towards building foundational AI capabilities for Hayden that will enable solving complex problems for Hayden AI ...

Matroid

Deep Learning Engineer

Palo Alto, CA · On-site

$170K - $300K/yr

We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the forefront of computer vision and deep learning applied to challenging, real-world use-cases. You will ...

Matroid

Deep Learning Engineer

Palo Alto, CA

We are looking for a world-class Deep Learning Software Engineer who is excited to operate at the forefront of computer vision and deep learning applied to challenging, real-world use-cases. You will ...

femtoAI

Audio Deep Learning Engineer

San Bruno, CA · On-site

About the Role As a Deep Learning Engineer, you will: * Design, develop, and deploy deep-learning-based and classical DSP audio algorithms for our SPU platform. * Leverage innovative model ...

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to join our R&D ...

Apply Early

Imagry

Senior Deep Learning Engineer - Perception

San Jose, CA · On-site

$123K - $169K/yr

Description Senior Deep Learning Engineer, Computer Vision imagry.E4.E30@comeetapply.com Location: San Jose, CA , On Site We are looking for a capable and experienced Sr. Deep Learning Engineer to ...

Nvidia

Senior Deep Learning Engineer

Santa Clara, CA

$65 - $83.75/hr

We are now looking for a Senior Deep Learning Engineer!At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking ...

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How much do deep learning engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for deep learning engineer in California is $114,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,900.00 and $149,500.00 per year, depending on experience, location, and employer.

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 Engineer or AI research director, often involving advanced skills in machine learning frameworks, data modeling, and large-scale system development. These roles usually require extensive experience, specialized knowledge, and may include leadership responsibilities or working in cutting-edge AI research environments.

What is a Deep Learning Engineer job?

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 are the key skills and qualifications needed to thrive in the Deep Learning Engineer position, and why are they important?

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 engineers make $500,000?

Senior engineers in high-demand fields such as software, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and data architects at large tech companies or startups often reach this compensation level through base salary, bonuses, and stock options.

What do deep learning engineers do?

Deep learning engineers develop and implement neural network models to solve complex problems such as image recognition, natural language processing, and speech analysis. They work with large datasets, use frameworks like TensorFlow or PyTorch, and often require knowledge of programming, mathematics, and machine learning principles.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

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 engineers make $300,000 a year?

Senior deep learning engineers and AI specialists with extensive experience, advanced skills in machine learning frameworks, and strong domain knowledge can earn $300,000 or more annually. These roles often require advanced degrees, certifications, and work in high-demand industries such as technology, finance, or healthcare, typically involving leadership responsibilities and complex project management.
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Deep Learning Engineer jobs near you
Deep Learning Engineer

Deep Learning Engineer

Hayden AI

San Francisco, CA • On-site

$161K - $175K/yr

Full-time

Posted 14 days ago

Job description

About Us
At Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.
From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future.
About the Deep Learning Team
The Deep learning team's work is at the crux of Hayden AI's solutions to its customers. The team is responsible for building and maintaining advanced models that are able to perceive the world and the knowledge produced by the models is used downstream to implement various customer use-cases. The team runs a number of models both in the cloud as well as on the edge device serving different scenarios. The team also works closely with the platform team to build out Hayden AI's MLOps infrastructure to achieve better scale and reliability.
About the Role
As a Deep Learning Engineer at Hayden, you will make key contributions towards building foundational AI capabilities for Hayden that will enable solving complex problems for Hayden AI Customers. In this role, you will build, train, evaluate and deploy state of the art ML models in production at scale. You will report into the Director of AI within the Perception Org and work closely with other engineering as well as product teams to deliver value to Hayden AI customers. We are looking for someone who has familiarity with or growing expertise in at least one of the verticals below - depth in a specific area is valued but not required on day one.
  1. 3D vision models to predict depth and 3D structure,
  2. Video/temporal behavior models to predict intent,
  3. Deep understanding of Vision language models and hands-on experience fine tuning them,
  4. Deep understanding of foundation models in perception.
  5. Deep knowledge of Nvidia edge device stack for running ML models and cuda know-how in terms delivering highly optimized models

This position is based in San Francisco and follows a hybrid schedule with at least 3 days in-office per week.
Key Responsibilities
Below are your primary responsibilities. These represent the core areas where you'll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.
  • Come up with solutions to complex problems in perception using deep learning.
  • Articulate ideas both verbally and in written form culminating in clear design and project plan docs for their work
  • Contribute to team roadmap and planning
  • Work with cross functional teams across the company and contribute towards delivery of end to end solutions for the customer

Required Qualifications
The qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.
  • Experience: 1-2 years experience building and deploying machine learning models for perception in production settings.
  • Core Skills: Solid hands-on experience designing, training, and evaluating machine learning models for perception. Demonstrated ability to independently build ML pipelines and deploy models to cloud environments (AWS, GCP, or Azure); familiarity with MLOps practices including experiment tracking, model versioning, and automated workflows. Hands-on experience in PyTorch, Python, and related skills.
  • Personal Attributes:Good communicator, self starter and ability to collaborate with others, quick learner who can adapt to a fast paced startup culture
  • Education: Bachelors or Masters in Computer Science or related field
  • Nice to Have: Experience working in perception problems in self driving car companies that aligns closely with the work of this team.

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