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Machine Learning Research Engineer Jobs in California

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: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct novel research to achieve results on Sohu, translating core mathematical operations into performant instruction sequences and ...

Etched

Machine Learning Research Engineer

Cupertino, CA · On-site

$252K/yr

The Machine Learning Research Engineer will propose and conduct research to optimize performance on Sohu, collaborating with hardware architects to develop software solutions that leverage the unique ...

Profluent

Machine Learning Research Engineer

Emeryville, CA · On-site +1

$237K/yr

We're looking for an experienced Machine Learning Engineer to build and improve the models and ML ... Partner with ML and protein design scientists to prototype research ideas and bring them into ...

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All JobsMachine Learning Research Engineer JobsMachine Learning Research Engineer Jobs in California

Machine Learning Research Engineer information

See California salary details

$36.5K

$104.6K

$140.6K

How much do machine learning research engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning research engineer in California is $104,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,600.00 and $102,600.00 per year, depending on experience, location, and employer.

What does a machine learning research engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are the key skills and qualifications needed to thrive as a machine learning research engineer?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What are some common challenges faced by machine learning research engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

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

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

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

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

Machine Learning Research Engineer jobs near you
Infographic showing various Machine Learning Research Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $104,624 per year, or $50.3 per hour.

Machine Learning Research Engineer

Convectivecapital

Redwood City, CA • On-site

$140 - $240/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 17 days ago

Job description

Machine Learning Research Engineer

WindBorne Systems is supercharging weather forecasts with a proprietary data source: a global constellation of next-generation smart weather balloons targeting critical atmospheric data. We design, manufacture, and operate our own balloons, using their observations to generate otherwise unattainable weather intelligence.

Our mission is to eliminate weather uncertainty and help humanity adapt to climate change—whether by predicting hurricanes or speeding the adoption of renewables. The founding team of Stanford engineers was named Forbes 2019 30 Under 30 and is backed by top-tier investors, including Khosla Ventures and Footwork VC.

WindBorne builds AI weather models that run 24/7, producing global forecasts every 20 minutes. Weather forecasting presents unusually rich machine learning problems: enormous, messy datasets; imperfect ground truth; complex physical structure; and models that must work reliably in the real world.

We are looking for a broadly capable ML researcher and engineer who is passionate about machine learning and excited to push our models forward. We care more about your ability to identify important problems and make progress on them than whether your previous work fits a particular specialty.

Responsibilities
  • AI-based data assimilation — Develop methods for incorporating real-time observations from balloons, satellites, weather stations, and other sources into our forecasts.
  • A foundation model for weather — Work toward a single model capable of predicting many weather-related datasets, including variables and data products not covered by traditional global forecasts.
  • Messy, large weather datasets — Find, understand, clean, and combine large datasets with inconsistent formats, resolutions, coverage, and quality. Determine which data is actually useful and build systems that make it easier to use again.
  • Rapid experiments — Test ideas quickly, learn from failures, and follow promising results into the weeds and chase down another 1% of model improvement.
  • Infrastructure and systems — Turn successful experiments into reusable systems that accelerate future research.
  • Research direction — Form hypotheses, design convincing experiments, keep up with relevant ML research, and help decide which ideas are worth pursuing.
  • Whatever the problem needs — Venture into operations, infrastructure, evaluation, data engineering, or other technical side quests when needed to get the research working in practice.
Skills and Qualifications
  • Strong research taste: you can identify important questions, design experiments that answer them, and recognize when a result is real.
  • Deep enthusiasm for machine learning and a desire to understand models in detail rather than treating them as black boxes.
  • Strong Python and PyTorch skills, with experience developing and debugging nontrivial ML systems.
  • Experience working with large, messy datasets and building dependable pipelines or abstractions around them.
  • Able to iterate quickly while thinking systematically about which work should become durable infrastructure.
  • Comfortable crossing boundaries between research and engineering and learning unfamiliar tools or domains as needed.
  • Experience with weather, climate, geospatial data, scientific machine learning, computer vision, or time-series forecasting is helpful, but not required.
Benefits
  • 401(k)
  • Dental, health, and vision insurance
  • Unlimited PTO
  • Stock Option Plan
  • Office food and beverages
Salary
  • $140k–$240k. We consider a range of backgrounds and experience levels and adjust offers to be competitive with market rates.
Location

1600 Bridge Pkwy, Redwood City, CA. Hybrid or in-person.

What our hardware looks like

WindBorne Systems is based in Redwood Shores, California. Our technology is invented, designed, and manufactured in the USA.

© 2026 by WindBorne Systems

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