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Internship Stochastic Modeling Jobs in California

... the ML model is the only stochastic component. We iterate fast (multiple robot generations in ... with strong project or internship experience are welcome to apply) * Strong programming ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

At RTX, our internships, co-ops and full-time careers provide an exceptional foundation to work on ... Develop, prototype, and test data link models and communication signal processing algorithms in ...

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Internship Stochastic Modeling information

What is an internship stochastic modeling?

Internship Stochastic Modeling positions are temporary roles designed for students or recent graduates to gain practical experience in applying stochastic processes and mathematical modeling techniques. Interns typically work under the guidance of experienced professionals in fields such as finance, insurance, engineering, or data science. They assist with analyzing data, developing models that incorporate randomness or uncertainty, and supporting decision-making processes. These internships provide valuable hands-on experience and help interns build skills in programming, statistical analysis, and problem-solving relevant to stochastic modeling careers.

What do internship stochastic modeling positions do?

As an intern in stochastic modeling, you will typically work on projects involving data analysis, model development, and simulation of random processes. Your daily tasks may include cleaning and organizing datasets, implementing mathematical models using programming languages like Python or R, and running simulations to test hypotheses. You will likely collaborate with senior modelers and data scientists, participate in team meetings, and may also present your findings. This role offers exposure to real-world applications in industries such as finance, insurance, or engineering, helping you develop both technical and communication skills.

What are the key skills and qualifications needed to thrive as an internship stochastic modeling?

To thrive in a Stochastic Modeling Internship, you need a solid background in probability, statistics, and mathematics, often supported by coursework or a degree in a quantitative field. Familiarity with programming languages such as Python, R, or MATLAB, and experience using statistical modeling software are typically expected. Strong analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and explaining complex concepts. These abilities ensure you can develop accurate models, collaborate with teams, and contribute valuable insights to data-driven decision-making processes.

What is the difference between Internship Stochastic Modeling vs Data Analyst?

AspectInternship Stochastic ModelingData Analyst
Required CredentialsRelevant coursework, basic programming skillsBachelor's in statistics, data science, or related field
Work EnvironmentInternship setting, research-focused, financial or tech industriesOffice environment, various industries including finance, marketing, healthcare
Employer & Industry UsageFinancial firms, tech companies, research institutionsCorporations, consulting firms, government agencies

Internship Stochastic Modeling typically involves applying probability and statistical techniques to model uncertainty, often in finance or research settings. Data Analysts focus on interpreting data, creating reports, and supporting decision-making across diverse industries. While both roles require analytical skills, stochastic modeling internships emphasize mathematical modeling, whereas data analyst roles focus on data manipulation and visualization.

What are the most commonly searched types of Stochastic Modeling jobs in California?

The most popular types of Stochastic Modeling jobs in California are:

What job categories do people searching Internship Stochastic Modeling jobs in California look for?

The top searched job categories for Internship Stochastic Modeling jobs in California are:

What cities in California are hiring for Internship Stochastic Modeling jobs?

Cities in California with the most Internship Stochastic Modeling job openings:

Software Engineer

Gradient Robotics

San Francisco, CA โ€ข On-site

Full-time

Re-posted 12 days ago


Key responsibilities

  • Ship performance-critical code to real robots daily.

  • Learn the full data flow from camera frames to perception, planning, control commands, and actuator feedback.

  • Contribute to the real-time control loop to maintain deterministic high-rate control alongside vision inference.


Job description

About the Company
The datacenter buildout is the largest industrial project in human history. Gradient builds the autonomous robots that make it possible.
Partnered with the world's largest AI infrastructure companies and backed by the industry's best investors, we move fast and build full-stack systems that matter.
About the role
We're looking for a Software Engineer to help move data from AI models to actuators. You'll work close to the hardware, from kernel and firmware up through the controls and perception layers, contributing to real-time pipelines that move hundreds of megabytes at single-digit millisecond latency. Vision inference, control loops, and actuation all live on the same clock, and you'll help keep them there. The goal: bring visibility and determinism into the end-to-end inference pipeline so the ML model is the only stochastic component. We iterate fast (multiple robot generations in months, not years), so the code you ship lands on real machines doing real precision work almost immediately.
Responsibilities
  • Ship performance-critical code to real robots daily
  • Learn the full data flow: camera frames in, perception and planning in the middle, control commands and actuator feedback out, and the systems that carry them
  • Contribute to the real-time control loop: help keep high-rate control running deterministically alongside vision inference
  • Build pieces of the perception data path: move high-bandwidth camera streams into the CV and ML models with minimal latency and zero silent drops
  • Push down latency and tighten the stack to make the system faster, more deterministic, and more reliable
  • Bring visibility into the pipeline: build tooling and instrumentation that make real-time behavior across controls and vision observable and debuggable
Minimum Qualifications
  • 1+ years of software engineering experience building systems close to hardware (exceptional new grads with strong project or internship experience are welcome to apply)
  • Strong programming fundamentals in at least one of Rust, C++, or Python, with solid understanding of operating systems and multithreading
  • Experience building things: production systems, internal tools, student teams, or personal projects that worked
  • Debugged real timing, concurrency, or hardware issues, even in a project setting
  • Comfort with ambiguity and a strong learn-by-doing instinct
  • Able to work on-site in San Francisco 5 days/week (6 days/week if needed during crunch time), embedded in the team
Preferred Qualifications
  • Linux kernel or embedded systems experience
  • Exposure to build and test infrastructure: Bazel, Nix, HIL testing, or CI/CD
  • Experience with real-time control systems: motor control, high-rate control loops, or robot controllers
  • Computer vision pipeline experience: camera drivers, image transport, GPU inference, or sensor synchronization
  • Tracing and profiling experience: ftrace, flamegraphs, eBPF
  • Comfort using AI tools to multiply your own output