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Remote Deep Learning Jobs in California (NOW HIRING)

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated ... We have hybrid offices in London, New York, and Singapore; this role is remote based in the San ...

Think Academy US

Learning Consultant

San Jose, CA · Remote

$25/hr

This role calls for strong communication, quick problem-solving, and a deep understanding of how to address client needs promptly and thoughtfully. As a Remote Learning Consultant, your ...

Think Academy US

Learning Consultant

San Jose, CA · Remote

$25/hr

This role calls for strong communication, quick problem-solving, and a deep understanding of how to address client needs promptly and thoughtfully. As a Remote Learning Consultant, your ...

Think Academy US

Learning Consultant

San Jose, CA · Remote

$25/hr

This role calls for strong communication, quick problem-solving, and a deep understanding of how to address client needs promptly and thoughtfully. As a Remote Learning Consultant, your ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$125K - $172K/yr

The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines ... remote. What You'll Do: * Implement and refine DL pipelines on distributed computing platforms ...

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All JobsRemote Deep Learning JobsRemote Deep Learning Jobs in California

Remote Deep Learning information

See California salary details

$21.1K

$128.3K

$209.6K

How much do remote deep learning jobs pay per year?

As of Jun 18, 2026, the average yearly pay for remote deep learning in California is $128,275.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,192.00 and $165,979.00 per year, depending on experience, location, and employer.

What is a Remote Deep Learning job?

A Remote Deep Learning job involves working with artificial intelligence and machine learning models, particularly using deep neural networks, from a location outside a traditional office, often from home. Professionals in this field design, build, and optimize algorithms that enable computers to learn from large amounts of data. They often work on projects such as image and speech recognition, natural language processing, or autonomous systems. The remote aspect allows flexibility and access to global opportunities, but requires strong communication skills and the ability to collaborate virtually with teams.

What are some common challenges faced by remote deep learning engineers, and how can they be addressed?

Remote deep learning engineers often encounter challenges such as limited access to high-performance computing resources, communication barriers with distributed teams, and difficulties in collaborating on large codebases or datasets. These issues can be mitigated by leveraging cloud-based platforms for scalable computing, using clear communication tools like Slack or Zoom for regular check-ins, and employing version control systems like Git for collaborative code management. Proactively setting up workflows and documentation helps ensure smooth collaboration and project continuity within a remote environment.

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

AspectRemote Deep LearningRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; experience with algorithms and data modeling
Work EnvironmentCollaborative teams, research-focused, often in tech or AI companiesDevelopment teams, data-driven projects, across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, e-commerce

Remote Deep Learning specialists focus on designing and training neural networks for AI applications, often requiring advanced knowledge of deep neural architectures. Remote Machine Learning Engineers work on developing algorithms and models for broader data analysis and predictive tasks. While both roles involve machine learning, deep learning emphasizes neural networks, whereas machine learning engineers may work with a variety of algorithms across industries.

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

To thrive as a Remote Deep Learning Engineer, you need strong programming skills in Python, a deep understanding of machine learning algorithms, and typically a degree in computer science, engineering, or a related field. Proficiency with frameworks like TensorFlow or PyTorch, as well as cloud computing platforms such as AWS or Google Cloud, is essential, and certifications in these technologies can be advantageous. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These skills ensure effective development, deployment, and maintenance of deep learning models while working independently in distributed teams.
What are the most commonly searched types of Deep Learning jobs in California? The most popular types of Deep Learning jobs in California are:
What are popular job titles related to Remote Deep Learning jobs in California? For Remote Deep Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning jobs in California look for? The top searched job categories for Remote Deep Learning jobs in California are:
What cities in California are hiring for Remote Deep Learning jobs? Cities in California with the most Remote Deep Learning job openings:
Remote Deep Learning jobs near you
Infographic showing various Remote Deep Learning job openings in California as of June 2026, with employment types broken down into 77% Full Time, 22% Part Time, and 1% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $128,275 per year, or $61.7 per hour.

Lead MD & MLIP Scientist - Equity & Remote Options

Azulenelabs

San Francisco, CA • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

A biotech startup in California is seeking a Chemical Physics expert to lead projects in molecular dynamics and enhanced sampling. The ideal candidate will have a PhD and strong expertise in deep learning, computational thermodynamics, and developing neural network potentials. This role offers substantial equity and the opportunity to engage in high-impact scientific work that has real-world consequences.

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