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Remote Deep Learning Jobs in California (NOW HIRING)

Senior AI Engineer

San Francisco, CA ยท On-site +1

$150K - $250K/yr

... neural networks, and deep learning algorithms that power our next-generation products ... Flexible work hours and remote work options * Topโ€‘tier equipment and home office setup

... Remote) No salary Not specified Senior (6-10 years) Post-Secondary Diploma/Certificate English ... Strong background in deep learning, computer vision, modeling and or supervised learning.

... remote. Professional Summary: The Principal Data Scientist will drive innovation across the full ... Initiate and lead novel research in machine learning and AI, especially in deep learning, large ...

Principal Data Scientist

Duarte, CA ยท Remote

$48 - $62/hr

... remote. Professional Summary: The Principal Data Scientist will drive innovation across the full ... Initiate and lead novel research in machine learning and AI, especially in deep learning, large ...

Senior Machine Learning Engineer

San Francisco, CA ยท On-site +1

$186K - $300K/yr

Develop and deploy deep learning models (Transformers, LSTMs, etc.) for forecasting and anomaly ... Employee divides their time between in-office and remote work. Access to an office location is ...

Bachelors in Computer Science or a similar discipline, or an equivalent amount of deep learning ... remote, the specific salary range for your preferred location, during the hiring process. Waymo ...

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Showing results 1-20

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 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:
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.
Senior Machine Learning Engineer - VLM/LLM Evaluation

Senior Machine Learning Engineer - VLM/LLM Evaluation

Waymo

San Francisco, CA โ€ข On-site, Remote

$204K - $259K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of safely operating Waymo vehicles in dozens of cities and under all driving conditions. As part of our work, we also initiate and foster collaborations with other research teams in Alphabet. AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical learning, and robust evaluation.

This role follows a hybrid work schedule and you will report to a Senior Staff Software Engineer.

You will:

  • Work with a creative team of people who help to build the state-of-the-art Foundation Models that are used throughout Waymo's systems, both onboard autonomous vehicles and offboard in simulation
  • Drive the development or significantly contribute to end-to-end evaluation systems and benchmarks for Waymo Foundation models, encompassing the entire life-cycle from pre-training and supervised fine-tuning (SFT) to reinforcement learning (RL), for evaluating the quality, safety, and realism of embodied AI agents
  • Partner with cross-functional teams within the organization to land innovative tech in production
  • Implement and extend large large scale data and evaluation pipelines.

You have:

  • Bachelor or Master's degree in Computer Science, similar technical field of study, or equivalent practical experience
  • Experience in ML engineering and applied Deep Learning
  • Experience with large scale distributed system
  • Proficient programming skills (eg: Python, C/C++)

We prefer:

  • ML infra experience: training, evaluating and deploying ML models at scale
  • Deep learning experience, especially with generative models, e.g., LLMs/VLMs, and/or reinforcement learning
  • Proficiency and in-depth knowledge of the inner workings of an ML framework (e.g. Pytorch, JAX, Tensorflow)

In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:

  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
  • Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range $204,000โ€”$259,000 USD