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Parallel Learning Jobs in California (NOW HIRING)

Apple Inc.

Machine Learning Compiler Engineer

Sunnyvale, CA · On-site

$150 - $190/hr

As a Machine Learning Compiler Engineer on the Apple Neural Engine (ANE) team, you'll work to bring ... Experience optimizing compilers for distributed, parallel, or heterogeneous execution environments ...

LLNL

Machine Learning Physics Graduate Student

Livermore, CA · On-site

$6.7K - $8.2K/mo

  • Retirement

Develop parallel C/C++/Python codes to train, test and evolve (a) PDEs (for phase field and phase ... Explore the use of machine learning methods to discover and evolve PDEs for phase field and phase ...

pony.ai

(Senior) Software Engineer, Deep Learning

Fremont, CA · On-site

$140K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Solid understanding of data structures, algorithms, parallel computing, code optimization and large scale data processing. * Experience in applied machine learning including data collection and ...

pony.ai

(Senior) Software Engineer, Deep Learning

Fremont, CA · On-site

$140K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Solid understanding of data structures, algorithms, parallel computing, code optimization and large scale data processing. * Experience in applied machine learning including data collection and ...

pony.ai

(Senior) Software Engineer, Deep Learning

Fremont, CA · On-site

$140K - $280K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Solid understanding of data structures, algorithms, parallel computing, code optimization and large scale data processing. * Experience in applied machine learning including data collection and ...

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Showing results 41-60

All JobsParallel Learning JobsParallel Learning Jobs in California

Parallel Learning information

See California salary details

$34.5K

$81.4K

$159.9K

How much do parallel learning jobs pay per year?

As of Aug 13, 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 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 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.

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 are the key skills and qualifications needed to thrive as a learning specialist at Parallel Learning?

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.
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 July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $81,427 per year, or $39.1 per hour.

Machine Learning Compiler Engineer

Apple Inc.

Sunnyvale, CA • On-site

$150 - $190/hr

Other

Re-posted 13 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Sunnyvale, California, United States Machine Learning and AI

At Apple, we're on the cutting edge of delivering transformative experiences through Artificial Intelligence. If you're passionate about pushing the boundaries of AI and hardware optimization, we want you to join our team! As a Machine Learning Compiler Engineer on the Apple Neural Engine (ANE) team, you'll work to bring high-performance, low-power AI solutions to life on iconic Apple products like the Vision Pro, iPhone, iPad, Mac, and more. This is a dynamic opportunity to work with us in a creative, collaborative environment while developing groundbreaking technologies that will shape the future of computing. Are you ready to help us deliver the next groundbreaking Apple products?

Description

As a Machine Learning Compiler Engineer, you will:

  • Architect and develop the compiler for Apple's proprietary Neural Engine Accelerator, optimizing it for deep learning inference with a focus on performance, scalability, and power efficiency
  • Collaborate with cross-functional teams, including hardware and platform architecture teams, to bring new hardware silicon to market and ensure compiler support for next‑gen features
  • Lead the design and implementation of complex compiler features, advancing both technical capabilities and strategic alignment across the team and company
  • Play an instrumental role in defining new compiler architecture approaches and optimizations, balancing trade‑offs between performance, energy efficiency, and hardware constraints
  • Identify and drive initiatives that will improve the scalability and general performance of AI workloads on Apple hardware, contributing to the vision and roadmap of the Apple Neural Engine team
Minimum Qualifications
  • Bachelor’s degree in Computer Science, Computer Engineering, or a related field with 3 years of relevant experience
  • Experience with program analysis and IR (Intermediate Representation), or programming language design, particularly with MLIR and LLVM
  • Proven expertise in compiler design and architecture, including deep experience with front‑end and middle‑end optimizations, register allocation, and back‑end code generation
  • High‑level proficiency in C++ and experience working with large, complex software systems
Preferred Qualifications
  • Master's or PhD degree in Computer Science, Computer Engineering, or a related field
  • Demonstrated ability to ship high‑quality production software
  • Strong communication skills and ability to collaborate effectively across teams and functions
  • Experience optimizing compilers for distributed, parallel, or heterogeneous execution environments, with a solid understanding of shared memory, synchronization, and multi‑threading techniques
  • Expertise in neural network inference on specialized SoCs or GPUs, and knowledge of deep learning frameworks and tools
  • Familiarity with Just-in-Time (JIT) compilation and dynamic optimization techniques for real‑time code execution

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

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What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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