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Internship Machine Learning Jobs in California (NOW HIRING)

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... • Strong background in machine learning engineering with a focus on model optimization ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

Required : • 4+ years of non-internship professional MLE experience. • Deep expertise in ... • Strong background in machine learning engineering with a focus on model optimization ...

We are currently hiring both full-time and interns to join our R&D team. Responsibilities: * Develop deep learning models for prototyping and production purposes according to product feature request

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Internship Machine Learning information

See California salary details

$25.2K

$42K

$86.8K

How much do internship machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for internship machine learning in California is $42,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning vs Data Science Intern?

AspectInternship Machine LearningData Science Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, programming, data analysis basics
Work EnvironmentHands-on ML model development, codingData analysis, visualization, reporting
Industry UsageTech, AI companies, research labsBusiness, finance, healthcare sectors

Internship Machine Learning focuses on developing and implementing machine learning models, requiring programming and ML fundamentals. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. Both roles are common in tech and research industries, but ML internships are more specialized in model building, while Data Science internships emphasize data analysis and visualization.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning, and why are they important?

To thrive as a Machine Learning Intern, you generally need a solid grounding in mathematics, programming (especially Python), and familiarity with machine learning concepts, often supported by coursework or relevant projects. Experience with tools and libraries like TensorFlow, scikit-learn, and Jupyter Notebooks, as well as knowledge of version control systems like Git, is typically expected. Strong problem-solving skills, willingness to learn, and effective communication set outstanding interns apart. These skills and qualities enable interns to contribute meaningfully to projects, adapt quickly, and collaborate well within technical teams.

What are internship machine learning positions?

Internship machine learning positions are temporary roles for students or recent graduates to gain hands-on experience in the field of machine learning. Interns typically work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced professionals. These internships provide valuable exposure to machine learning tools, programming languages such as Python, and industry best practices. They are an excellent way to build technical skills, enhance your resume, and explore career opportunities in artificial intelligence and data science.

What types of projects can I expect to work on during a Machine Learning internship?

As a Machine Learning intern, you may work on a variety of projects such as data preprocessing and cleaning, developing and testing machine learning models, or assisting with research experiments. These projects often involve collaborating closely with data scientists and engineers, learning to use popular frameworks like TensorFlow or PyTorch, and presenting your findings to the team. The scope and complexity of your assignments will typically grow as you demonstrate proficiency and initiative, providing valuable real-world experience and networking opportunities.
What are the most commonly searched types of Machine Learning jobs in California? The most popular types of Machine Learning jobs in California are:
What job categories do people searching Internship Machine Learning jobs in California look for? The top searched job categories for Internship Machine Learning jobs in California are:
What cities in California are hiring for Internship Machine Learning jobs? Cities in California with the most Internship Machine Learning job openings:
Machine Learning Engineer - Model Inference

Machine Learning Engineer - Model Inference

Apple

Cupertino, CA

$150K - $277K/yr

Full-time

Medical, Dental, Retirement

Posted 5 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Join Apple Maps to help build the best map in the world! In this role on our ML Platform Team, you will leverage advanced deep learning and large language models to improve the search quality and overall customer experiences across our various Maps platforms. This role offers amazing opportunities to partner closely with research and product teams while taking ownership of projects and delivering measurable results at a global scale!
Description
As a member of our team, you will help design, build, and operate the services used to deploy and serve machine learning models at scale. You will help oversee the infrastructure that powers model inference, from developing high-performance serving systems to implementing optimization techniques that reduce latency, increase throughput, and improve hardware utilization. Get excited about collaborating closely with machine learning researchers, infrastructure engineers, and product teams to transform new models into reliable, production-ready experiences.
This role will require you to communicate technical ideas clearly, and to present design decisions and performance findings to both technical and cross-functional audiences. You will also participate in collaborative discussions, design reviews, and project planning meetings.
.
We encourage our team-members to learn quickly, take ownership of meaningful projects, and contribute ideas that improve both the performance of our systems and the experiences of the people who use them!
","responsibilities":"Design, implement, test, and maintain scalable machine learning inference services.
Improve inference latency, throughput, availability, and infrastructure efficiency.
Develop benchmarking and profiling tools to identify performance bottlenecks.
Develop techniques such as dynamic batching, caching, quantization, pruning, model compilation, and parallel execution.
Work with machine learning frameworks, inference runtimes, GPUs, and other hardware accelerators.
Build monitoring, logging, alerting, and load-testing capabilities for production services.
Investigate reliability and performance issues across models, software runtimes, and infrastructure.
Write clear, maintainable code and participate in design reviews, code reviews, and operational support.
Preferred Qualifications
Experience with model serving technologies such as Triton, TensorRT, ONNX Runtime, vLLM, TensorFlow Serving, or TorchServe.
Familiarity with inference optimization techniques, including quantization, pruning, knowledge distillation, speculative decoding, kernel fusion, or continuous batching.
Understanding of GPUs, accelerators, distributed systems, networking, or high-performance computing.
Familiarity with containers, Kubernetes, cloud infrastructure, and production observability tools.
Experience benchmarking large language models, vision models, or other compute-intensive machine learning workloads.
Possess curiosity about how software, models, and hardware interact to determine real-world performance.
Minimum Qualifications
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field plus at least 2 years of post graduate work experience.
Strong programming skills in Python and at least one systems-oriented language such as C++, Rust, or Go.
Solid understanding of data structures, algorithms, operating systems, and computer architecture.
Familiarity with machine learning fundamentals and modern deep learning frameworks such as PyTorch, TensorFlow, or JAX.
Experience building, debugging, or evaluating software systems through coursework, internships, research, open-source contributions, or personal projects.
Ability to analyze technical problems, communicate clearly, and work effectively with engineers across multiple disciplines.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

Hours and flexibility

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Get the full story on Breakroom


Apple logo

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