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Parallel Learning Jobs in California (NOW HIRING)

Pony.ai

(Senior) Software Engineer, Deep Learning

Fremont, CA · On-site

$134.50K - $177.30K/yr

... optimizing deep learning models for real-time applications. Responsibilities : • Work with ... parallel computing, code optimization and large scale data processing. • Experience in applied ...

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Parallel Learning information

See California salary details

$34.5K

$81.4K

$159.9K

How much do parallel learning jobs pay per year?

As of May 31, 2026, the average yearly pay for parallel learning in California is $81,427.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,900.00 and $106,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Learning Specialist at Parallel Learning, and why are they important?

To thrive as a Learning Specialist at Parallel Learning, you generally need a background in education, special education, or psychology, often with relevant state certification or licensure. Familiarity with digital assessment tools, remote learning platforms, and individualized education program (IEP) software is typically required. Exceptional interpersonal skills, patience, and adaptability distinguish top performers in supporting diverse learners and collaborating with families and teams. These skills ensure personalized, effective interventions and help students reach their educational goals in a virtual environment.

How does a professional in Parallel Learning typically collaborate with educators, families, and specialists to support student success?

Professionals in Parallel Learning, such as educational therapists or learning specialists, play a key role in fostering collaboration between students, educators, families, and other specialists. They often coordinate with teachers to adapt curriculum, communicate with families about progress and strategies, and consult with speech-language pathologists or occupational therapists as needed. This interdisciplinary teamwork ensures that interventions are aligned and that each student receives consistent, individualized support. Regular meetings, progress updates, and shared goal-setting are common practices in this collaborative environment.

What is parallel learning?

Parallel learning is an educational approach where students receive supplemental instruction or interventions alongside their regular classroom learning. This method is often used to provide personalized support, such as special education services or targeted skill development, without removing students from their standard curriculum. By running interventions 'in parallel' with general education, students can address specific learning needs while staying engaged with their peers. Parallel learning can take many forms, including small group sessions, individualized instruction, or online modules.

What is the difference between Parallel Learning vs Data Analysis?

AspectParallel LearningData Analysis
Required CredentialsOften requires knowledge of machine learning, programming, and statisticsTypically requires statistics, Excel, and data visualization skills
Work EnvironmentTech-focused, research, and development settingsBusiness, finance, healthcare, and various industries
Employer & Industry UsageTech companies, startups, research institutionsCorporations, consulting firms, government agencies
Common Search & Comparison IntentUnderstanding roles related to machine learning and AIAnalyzing data to inform business decisions

Parallel Learning involves developing machine learning models and algorithms, often in tech or research environments, requiring programming and statistical skills. Data Analysis focuses on examining datasets to extract insights, used across many industries like finance and healthcare. While both roles involve working with data, Parallel Learning emphasizes creating models, whereas Data Analysis emphasizes interpreting data for decision-making.

What are popular job titles related to Parallel Learning jobs in California? For Parallel Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Parallel Learning jobs in California look for? The top searched job categories for Parallel Learning jobs in California are:
What cities in California are hiring for Parallel Learning jobs? Cities in California with the most Parallel Learning job openings:
Parallel Learning jobs near you
Infographic showing various Parallel Learning job openings in California as of May 2026, with employment types broken down into 52% Full Time, 40% Part Time, and 8% Nights. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $81,427 per year, or $39.1 per hour.
Senior Scientific Machine Learning Engineer - Earth-2

Senior Scientific Machine Learning Engineer - Earth-2

Nvidia

Santa Clara, CA

Full-time

Posted 23 days ago

Job description

NVIDIA's deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world's largest Internet companies. We need passionate and creative people to help us build the AI frameworks underlying the NVIDIA Earth-2 platform: a comprehensive family of open models, libraries, and frameworks that democratize global access to professional-grade weather and climate AI.

What you'll be doing:

  • Work with some of the brightest minds in a premier AI company to develop leading machine learning frameworks, NVIDIA PhysicsNeMo and NVIDIA Earth2Studio, for our academic and industrial partners to build scientific ML technology and workflows for weather, climate, and earth system modeling.

  • Work with internal project teams to validate applications built using the framework on NVIDIA's products, and integrate new functionalities from internal or external projects into the platform

  • Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's Earth-2 technologies, with a focus on weather & climate AI

What we need to see:

  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience

  • 5+ yrs of relevant experience

  • Strong Python programming skills

  • Familiarity with containers, numeric libraries, modular software design

  • Deep knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)

  • Experience with development and application of machine learning techniques to solve real world scenarios in weather/climate

  • Experience with scientific visualization. Strong analytical skills with bias for action

  • Good time-management and organization skills to thrive in a fast paced, dynamic environment

  • Solid written and oral communications skills. Good teamwork and interpersonal skills

Ways to stand out from the crowd:

  • Experience using multi-node systems with data-parallel and model-parallel programming, performance optimization. Experience with HPC programming models (OpenMPI, NCCL), and/or CUDA or GPU kernel programming

  • Experience with nonlinear simulation tools and techniques, usage of major simulation codes. Published papers in the field of AI in scientific computing, especially in weather & climate applications

  • Familiarity with common tooling in the Earth-2 ecosystem (xarray, zarr, regridding, weather & climate data stores, etc.)

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and establish teams with the most thoughtful people in the world.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 1, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning
Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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