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Machine Learning Engineer Opt Jobs in San Ramon, CA

... engineers across Apple.","responsibilities":"Design, train and tune machine learning algorithms, support camera architects to drive innovative solutions for imaging and sensing challenges, and ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Machine Learning Engineer

San Jose, CA · On-site

$96K - $128K/yr

We are looking for a Machine Learning Engineer to join our team of driven machine learning and software engineers. This role covers system design, prompt engineering, ML model evaluation, building ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$187K - $260K/yr

Special Skill Requirements: 1.) Machine Learning; 2.) TensorFlow; 3.) Python and SQL; 4.) Feature Engineering and Selection; 5.) Ads predictive model design; 6.) Ads predictive model offline training ...

About the role We're looking for Machine Learning Engineers to help build our platform for training, evaluating, and deploying interpretable AI systems at scale. You'll play a central role in ...

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Showing results 1-20

Machine Learning Engineer Opt information

See San Ramon, CA salary details

$35.2K

$143.9K

$216.2K

How much do machine learning engineer opt jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning engineer opt in San Ramon, CA is $143,902.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,400.00 and $173,200.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in San Ramon, CA? For Machine Learning Engineer Opt jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in San Ramon, CA look for? The top searched job categories for Machine Learning Engineer Opt jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Machine Learning Engineer Opt jobs? Cities near San Ramon, CA with the most Machine Learning Engineer Opt job openings:
Infographic showing various Machine Learning Engineer Opt job openings in San Ramon, CA as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $143,902 per year, or $69.2 per hour.
Machine Learning Engineer

Machine Learning Engineer

Apple

Sunnyvale, CA

$150K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 16 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 667 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Do you love taking on big challenges that require exceptionally creative solutions?
The Camera & Depth Architecture organization is responsible for research, design, and specifications of cameras and sensors for iPhone and other Apple products. As part of our machine learning team, you will play a vital role in prototyping foundational machine learning tools that bridge the camera hardware and software, in order to build flawless camera technology innovations and experiences that we are known worldwide.
Description
In this role, you will innovate foundational machine learning algorithms for computational photography and computer vision, to research, design and qualify novel cameras and sensors for future Apple products, in collaboration with a wide spectrum of top engineers across Apple.","responsibilities":"Design, train and tune machine learning algorithms, support camera architects to drive innovative solutions for imaging and sensing challenges, and provide data-driven feedback for future camera architectures across a wide spectrum of Apple products.
Work closely with cross functional teams to build computational imaging and machine learning prototypes for future Apple products that enable novel photography experiences.
Build differentiable simulation and physics-informed machine learning pipelines to analyze and improve cameras and sensors.
Ground the exploration via validated simulation and metrology results to avoid machine learning domain gaps and ensure production feasibility.
Preferred Qualifications
MS/PhD in computer vision, electrical, optical or computer engineering or related fields.
Experience or strong personal curiosity with designing imaging and sensing systems.
Strong independent problem-solving and communication skills.
Solid understanding of machine learning, deep learning fundamentals and optimizations; practical expertise in designing, training and improving deep neural networks.
Experience with cutting edge computer vision and machine learning research trends and models.
Experience with two or more of the following: ISP (image signal processing), 3A (AE, AF, AWB), diffusion models, multi-modal, generative AI, sensor fusion, sensor physics, differentiable rendering, 3D rendering.
Minimum Qualifications
BS in electrical, optical or computer engineering/science, and a minimum of 3 years relevant industry experience
Experience with software coding in Python.
Experience with one of the following: machine learning/deep learning systems, computer vision, graphics, computational imaging applications.
Experience with Pytorch.
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.

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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