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Postdoctoral Fellow Machine Learning Jobs in California

UC San Diego

Moore Postdoctoral Fellowship

San Diego, CA · On-site

$69K - $71K/yr

Moore Postdoctoral Fellow Salary range: A reasonable salary range estimate for this position is $69 ... Develop and train machine learning architectures using reduced-order predictions together with ...

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Postdoctoral Fellow Machine Learning information

What is a postdoctoral fellow in machine learning?

A Postdoctoral Fellow in Machine Learning is a researcher who has recently completed their PhD and is engaged in advanced research in the field of machine learning. This role typically involves conducting independent or collaborative research, publishing scientific papers, and sometimes mentoring students. Postdoctoral fellows often work at universities, research institutes, or industry labs, focusing on developing new algorithms, improving existing models, or applying machine learning techniques to specific problems. The position is usually temporary, lasting one to three years, and aims to prepare researchers for permanent academic or industry roles.

What is the difference between Postdoctoral Fellow Machine Learning vs Postdoctoral Research Scientist?

AspectPostdoctoral Fellow Machine LearningPostdoctoral Research Scientist
Required credentialsPhD in Computer Science, Data Science, or related fieldPhD in relevant field, often with specialized research experience
Work environmentAcademic labs, universities, research institutionsResearch labs, industry R&D departments, tech companies
Employer and industry usagePrimarily academia, government researchPrimarily industry, corporate research divisions
Common search and comparison intentUnderstanding academic research roles in machine learningExploring industry-focused research career paths

Postdoctoral Fellow Machine Learning roles typically focus on academic research, requiring a PhD and working in universities or research institutions. In contrast, Postdoctoral Research Scientist positions are often industry-based, emphasizing applied research within corporate R&D departments. Both roles involve advanced machine learning expertise but differ mainly in work environment and career trajectory.

What are the key skills and qualifications needed to thrive as a postdoctoral fellow in machine learning?

To thrive as a Postdoctoral Fellow in Machine Learning, you need a strong background in computer science, mathematics, and statistics, typically supported by a PhD and relevant research experience. Familiarity with programming languages such as Python, machine learning frameworks like TensorFlow or PyTorch, and experience in high-performance computing environments are commonly required. Strong analytical thinking, effective scientific communication, and collaboration skills help you contribute to research teams and disseminate findings. These skills and qualities are crucial for advancing research, developing innovative solutions, and building a successful academic or industry career in machine learning.

What are some common challenges faced by postdoctoral fellows in machine learning, and how can they be addressed?

Postdoctoral Fellows in Machine Learning often encounter challenges such as balancing independent research with collaborative projects, staying current with rapidly evolving technologies, and securing funding or publishing in top-tier journals. To address these, it's helpful to establish clear communication with mentors and collaborators, set aside dedicated time for reading recent literature, and actively seek feedback on research drafts. Building a professional network through conferences and seminars can also open opportunities for collaboration and career advancement.
What are popular job titles related to Postdoctoral Fellow Machine Learning jobs in California? For Postdoctoral Fellow Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Postdoctoral Fellow Machine Learning jobs in California look for? The top searched job categories for Postdoctoral Fellow Machine Learning jobs in California are:
What cities in California are hiring for Postdoctoral Fellow Machine Learning jobs? Cities in California with the most Postdoctoral Fellow Machine Learning job openings:
Postdoctoral Fellow Machine Learning jobs near you

Rainmaker Fellow, Machine Learning

Rainmaker Technology Corporation

El Segundo, CA • On-site, Remote

Full-time

Medical, Dental, Vision

Posted 12 days ago

Job description

About Rainmaker

Rainmaker is pioneering a modern cloud-seeding system to increase precipitation, improve water availability, and address severe-weather challenges. We combine atmospheric science, weather-resistant UAS, radar and satellite observations, numerical weather prediction, novel sensing systems, and sustainable seeding technologies to design, operate, and evaluate precipitation-enhancement programs.

Rainmaker collects unusual atmospheric datasets because we build sensors, operate aircraft, fly into clouds, and deliberately intervene in atmospheric systems. Our long-term advantage depends on turning those observations into better estimates, forecasts, and operational decisions.

About the Fellowship

The Rainmaker Machine Learning Fellowship is a paid, full-time research appointment for exceptional undergraduate and graduate students, postdoctoral researchers, recent graduates, and other early-career researchers.

As a fellow, you will join Rainmaker's R&D team and work alongside our researchers on a scoped machine-learning project drawn from Rainmaker's current research priorities and defined in close collaboration with your research lead or mentor. Project matching will consider available data, mentor capacity, team needs, and your background. You will take responsibility for a concrete workstream while contributing to the broader team's research, reviews, and technical decisions.

You will work with real sensor and operational data, establish credible baselines, build and evaluate models, and leave behind a durable dataset, system, or research artifact that Rainmaker can continue using. Fellows are not expected to arrive with an independent research agenda or define a project in isolation.

Rainmaker is accepting expressions of interest while aggressively building its dedicated ML capability. Applications may be reviewed before a specific project and start date are finalized. A fellowship will begin only after the fellow is matched with a ready project, usable data, and a credible hands-on ML mentor.

Examples of the Work

Fellowship projects change with Rainmaker's research and operational priorities. Examples of the work our ML team may pursue include:

  • Developing a short-range supercooled liquid water opportunity forecast using public NWP and Rainmaker observations.
  • Predicting hail-core growth, motion, splitting, and decay from radar sequences.
  • Building a bounded multimodal atmospheric-state reconstruction pilot.
  • Improving microwave-sounder retrievals using Rainmaker observations.
  • Modeling another scientific or operational problem selected with Rainmaker's ML and atmospheric-science teams.
What You'll Do
  • Translate a scientific or operational question into a measurable ML problem.
  • Build or improve the training and validation dataset needed for the project.
  • Establish simple, reproducible baselines before introducing more complex models.
  • Train, evaluate, and debug models using held-out weather events, regions, or operating conditions.
  • Quantify calibration, uncertainty, generalization, failure modes, and sensitivity to missing or biased data.
  • Work closely with atmospheric scientists to define useful targets, ground truth, physical constraints, and operational success criteria.
  • Produce clear, reusable code and documentation.
  • Present your results to Rainmaker's scientists, engineers, operators, and technical leadership.
  • Deliver a final artifact such as a benchmark dataset, model, prototype product, evaluation report, or research paper.
What We're Looking For
  • Current undergraduate, master's, or PhD students; postdoctoral researchers; recent graduates; and other early-career researchers are all eligible.
  • Strong Python programming ability and experience with a modern ML framework.
  • Evidence that you can independently build, test, and debug technical work.
  • Strong quantitative reasoning and an ability to design credible experiments.
  • Interest in noisy, sparse, multimodal, spatial, temporal, or physical data.
  • Ability to make progress on ambiguous research problems while incorporating mentor feedback.
  • Clear written and verbal communication.
  • Availability for full-time, on-site work in El Segundo for the agreed appointment.
Particularly Relevant Backgrounds
  • Machine learning, computer science, applied mathematics, statistics, physics, meteorology, remote sensing, robotics, autonomy, geospatial analysis, or scientific computing.
  • Forecasting, sequence modeling, computer vision, state estimation, sensor fusion, probabilistic modeling, data assimilation, or uncertainty quantification.
  • Weather knowledge is valuable but not required.
What Success Looks Like

By the end of the fellowship, you will have answered a clearly defined technical question and produced a rigorous, reusable result that advances the team's work. Depending on the project, that might be a benchmark dataset, evaluated model, prototype product, forecasting or retrieval improvement, or a well-supported analysis of performance and failure modes.

Success does not require a positive scientific result. A well-supported finding that the available data cannot answer the question-and a concrete recommendation for what Rainmaker should measure next-can be highly valuable.

Fellowship Details
  • Paid, full-time, and on-site in El Segundo.
  • Three-to-six-month appointment, with four months as the standard duration.
  • Rolling applications and flexible start dates based on project and mentor readiness.
  • Possible consideration for future full-time roles, without any promise or expectation of conversion.
Compensation and Benefits

$8,000 per month

Benefits:

  • Full health coverage (medical, dental, and vision insurance)
  • Lunch provided when working in-office and a fully stocked kitchenette
  • Free EV charging at the HQ
$8,000 - $8,000 a month
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