ZipRecruiter

Log In

2

Remote Applied Mathematics Intern Jobs in California

Veracyte

Principal Data Scientist

San Diego, CA · Remote

$210K/yr

PhD in Data Science, Machine Learning, Applied Math or equivalent field. * 8+ years of experience ... This is a remote friendly position for both US and Canada based candidates. * On-site desk-space is ...

Career Renew

Senior ML Engineer

San Francisco, CA · Remote

$180K - $240K/yr

You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ... Remote-first with strong perks -- flexible vacation, paid sabbatical after 5 years, comprehensive ...

previous page

Showing results 41-60

All JobsApplied Mathematics Intern JobsRemote Applied Mathematics Intern JobsRemote Applied Mathematics Intern Jobs in California

Remote Applied Mathematics Intern information

Is applied math in demand?

Applied mathematics is in high demand across industries such as finance, data science, engineering, and technology, where analytical and problem-solving skills are essential. Roles like remote applied mathematics interns often require proficiency in programming tools like MATLAB or Python and a strong foundation in mathematical modeling, making these skills valuable in the job market.

Is it possible to get a remote applied mathematics internship?

Yes, remote applied mathematics internships are available at many organizations, especially in tech, finance, and research sectors. These internships often require strong analytical skills, proficiency in programming tools like Python or MATLAB, and a background in mathematics or related fields. Applicants should review specific company requirements and application deadlines for remote opportunities.

What jobs can you get with a remote applied mathematics intern?

A remote applied mathematics intern can pursue roles such as data analyst, quantitative analyst, operations researcher, or research assistant. These positions often require skills in programming, statistical analysis, and problem-solving, and may be found in industries like finance, technology, or research organizations.

Which internship is best for applied mathematics students?

The best internship for applied mathematics students is one that offers hands-on experience in data analysis, modeling, or computational methods, often within industries like finance, technology, or research institutions. Internships that require proficiency in programming languages such as Python or MATLAB and provide mentorship or project-based work are highly valuable for skill development and career growth.

What are the most commonly searched types of Remote Applied Mathematics jobs in California?

The most popular types of Remote Applied Mathematics jobs in California are:

What are popular job titles related to Remote Applied Mathematics Intern jobs in California?

For Remote Applied Mathematics Intern jobs in California, the most frequently searched job titles are:

What job categories do people searching Remote Applied Mathematics Intern jobs in California look for?

The top searched job categories for Remote Applied Mathematics Intern jobs in California are:

What cities in California are hiring for Remote Applied Mathematics Intern jobs?

Cities in California with the most Remote Applied Mathematics Intern job openings:

Remote Applied Mathematics Intern jobs near you
Infographic showing various Remote Applied Mathematics Intern job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 16% Part Time, and 1% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution.

Rainmaker Fellow, Machine Learning

Rainmaker Technology Corporation

El Segundo, CA • On-site, Remote

Full-time

Medical, Dental, Vision

Posted 25 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.

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
apply for this job

Apply