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Deep Learning Engineer Jobs in California (NOW HIRING)

Matroid

Deep Learning Field Engineer

Palo Alto, CA · On-site

They are seeking a Deep Learning Field Engineer to develop and deploy cutting-edge CV systems that utilize deep learning techniques to address various industrial challenges. Responsibilities : • ...

PROPRIUS

Machine Learning Engineer

San Francisco, CA · On-site

You will implement state-of-the-art deep learning techniques to help develop innovative AI products. As a ML Engineer, you will: * Work with the research team to improve the visual search products

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 · 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 ...

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 ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

As a Senior Machine Learning Engineer, you will design, build, and scale advanced software systems ... Responsibilities : • Research, develop and deploy cutting-edge deep learning models, including ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Responsibilities : • Research, develop and deploy cutting-edge deep learning models, including ...

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Showing results 21-40

All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in California

Deep Learning Engineer information

See California salary details

$37.5K

$114.3K

$189K

How much do deep learning engineer jobs pay per year?

As of Aug 16, 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 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 the most commonly searched types of Deep Learning Engineer jobs in California?

The most popular types of Deep Learning Engineer jobs in California are:

What are popular job titles related to Deep Learning Engineer jobs in California?

For Deep Learning Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Deep Learning Engineer jobs in California look for?

The top searched job categories for Deep Learning Engineer jobs in California are:

What cities in California are hiring for Deep Learning Engineer jobs?

Cities in California with the most Deep Learning Engineer job openings:

Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in California 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 $114,347 per year, or $55 per hour.

Deep Learning Field Engineer

Matroid

Palo Alto, CA • On-site

Full-time

Re-posted 15 days ago

Job description

Job Summary:
Matroid is a company focused on building intuitive products for deploying computer vision models. They are seeking a Deep Learning Field Engineer to develop and deploy cutting-edge CV systems that utilize deep learning techniques to address various industrial challenges.
Responsibilities:
• Train state-of-the-art CV models across a broad range of domains, such as object detection, anomaly detection, panoptic segmentation, action recognition and tracking.
• Deploy end to end CV systems across a range of environments (cloud, edge, hybrid).
• Integrate Matroid into inspection workflows and third party systems, such as manufacturing execution systems, safety alert systems and video management systems.
• Perform quantitative and qualitative evaluation of the CV system and iterate on it to meet performance requirements.
• Act as the technical expert, advising on all matters from technical scoping of engagements to model training, deployment and integration.
• Empower customers with CV by designing and leading product training sessions.
Qualifications:
Required:
• Bachelor’s degree in computer science, computer engineering, electrical engineering, or another technical field.
• Experience training and deploying state-of-the-art CV models using popular machine learning frameworks, such as TensorFlow or PyTorch.
• Strong software engineering skills.
• Solid oral, written, presentation, collaboration, and interpersonal communication skills.
• Adept at communicating to both technical and commercial audiences.
Preferred:
• Graduate degree with a concentration in CV, artificial intelligence, machine learning, or related fields.
• Previous work experience in field engineering, professional services, consulting, or another customer-facing field.
• Experience with high growth technology startups.
Company:
Matroid provides a studio to create, combine, and use computer vision detectors, without programming. Founded in 2016, the company is headquartered in Palo Alto, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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