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Distributed Machine Learning Research Jobs (NOW HIRING)

Apple

AIML - Machine Learning Research

Seattle, WA

$142K - $263K/yr

As part of this group, you will be doing large scale machine learning and deep learning research and development to improve Open Domain Question Answering (using both structured knowledge graph data ...

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 ... distributed inference/training environments • Experience working cross-functionally in diverse ...

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 ... distributed inference/training environments • Experience working cross-functionally in diverse ...

Qualcomm

Machine Learning Researcher

San Diego, CA · On-site

... distributed/federated learning, and quantum machine learning). • Develops and publishes research findings in the form of presentations and conference papers. • Conducts research on machine ...

Qualcomm

Machine Learning Researcher

San Diego, CA · On-site

... distributed/federated learning, and quantum machine learning). • Develops and publishes research findings in the form of presentations and conference papers. • Conducts research on machine ...

Qualcomm

Machine Learning Researcher

San Diego, CA · On-site

$150 - $200/hr

Performs platform research to enable new machine learning compute paradigm (e.g., compute in memory, on‑device learning/training, edge‑cloud distributed/federated learning, and quantum machine ...

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

D. or equivalent experience in Computer Science, Machine Learning, Operations Research, or related fields. * Demonstrated experience working in cross-functional teams bridging ML research with ...

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 ... Experience with distributed training (DDP, FSDP, multi-node GPU clusters) * Experience with ...

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How much do distributed machine learning research jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for distributed machine learning research in the United States is $22.22, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $23.80 per hour, depending on experience, location, and employer.

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Infographic showing various Distributed Machine Learning Research job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,222 per year, or $22.2 per hour.

Machine Learning Research Engineer

Redwood City, CA • On-site

Convectivecapital
See more jobs at Convectivecapitalexternal

$150 - $200/hr

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 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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