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Machine Learning Testing Jobs in California (NOW HIRING)

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Conduct rigorous model evaluation, testing, and iteration to continuously improve model quality and ...

Machine Learning Engineer

Encino, CA · On-site

$129.10K - $208.83K/yr

Machine Learning Engineer At Palo Alto Networks ® , we're united by a shared mission--to protect ... testing. Compensation Disclosure: The compensation offered for this position will depend on ...

They are seeking a Machine Learning Engineer to design, build, and optimize backend services that ... testing, CI/CD, version control, and code review best practices. • Experience taking ML-powered ...

Contribute to the design of data pipelines and infrastructure for training, testing, and validating ... Stay current with the latest Machine Learning research for wireless and embedded systems. * Perform ...

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish ... Strong software engineering skills; knowledge of best practices, testing, and deployment Bonus ...

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish ... Strong software engineering skills; knowledge of best practices, testing, and deployment Bonus ...

Our most complex system is our risk model, your day to day will include feature generation and model training using machine learning techniques, developing A/B testing procedures, implementing ...

Machine Learning Analyst

Torrance, CA

$88.30K - $111.40K/yr

Senior Machine Learning Analyst The Senior Machine Learning Analyst will play a critical role in ... Conduct model validation, testing, and monitoring to maintain reliability. Qualifications Education:

Our most complex system is our risk model, your day to day will include feature generation and model training using machine learning techniques, developing A/B testing procedures, implementing ...

Our most complex system is our risk model, your day to day will include feature generation and model training using machine learning techniques, developing A/B testing procedures, implementing ...

Expertisein implementingMLOpspractices, including setting up continuous integration (CI), continuous delivery (CD), automated testing, and deployment pipelines for machine learning models. * Strong ...

... testing metrics. * Generate Actionable Insights: Enable the system to synthesize complex data ... Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language ...

Machine Learning Engineer III

Poway, CA · On-site

$116.48K - $208.51K/yr

Completes programming and implements efficiencies, performs testing and debugging. * Completes ... Adapts machine learning to areas such as virtual reality, augmented reality, artificial ...

Machine Learning Engineer Creatify is building the world's first end-to-end AI advertising agent--a ... to testing, optimization, and publishing across Meta, TikTok, YouTube, and more. In just 18 months ...

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Machine Learning Testing information

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How much do machine learning testing jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for machine learning testing in California is $22.52, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $25.14 per hour, depending on experience, location, and employer.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

What are the key skills and qualifications needed to thrive in the Machine Learning Testing position, and why are they important?

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.
Machine Learning Engineer

Machine Learning Engineer

Apple

Cupertino, CA

$212K - $318.40K/yr

Full-time

Medical, Dental, Retirement

Posted 28 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine learning solutions from research and experimentation through to robust, production-grade deployment.
Description
The MLE will collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. This hire will design end-to-end AI/ML solutions with clear business impact, from concept to deployment, with a strong focus on feasibility, scalability, and performance. You will benchmark, adapt, and integrate AI/ML models into existing systems.","responsibilities":"Deploy, monitor, and support AI tools in production environments, ensuring reliability and performance.
Contribute to the ongoing improvement of ML infrastructure, tooling, and best practices.
Partner with data scientists, and engineers to translate business requirements into technical ML solutions.
Conduct rigorous model evaluation, testing, and iteration to continuously improve model quality and efficiency.
Design and integrate LLM-powered features and AI agent workflows into production systems, ensuring reliability, scalability, and performance.
Build and maintain agentic pipelines that leverage tool use, memory, and multi-step reasoning to automate complex business processes.
Evaluate and benchmark LLM outputs as part of the model evaluation lifecycle, assessing quality, latency, and safety in production contexts.
Preferred Qualifications
10 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.
Solid understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.
Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML solutions.
Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams.
Familiarity with LLM evaluation practices including output quality assessment, hallucination detection, and latency benchmarking in production environments.
Minimum Qualifications
8 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.
Bachelor's Degree in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.
Proficiency in one or more object-oriented programming languages such as Python, Java, or C++, with hands-on experience building distributed systems.
Experience building large-scale machine learning systems using big data technologies such as Spark, SQL, Snowflake, or similar platforms.
Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Familiarity with MLOps practices including model versioning, CI/CD pipelines, and experiment tracking tools such as MLflow or similar.
Experience building and deploying applications using large language models (e.g., GPT-4, Claude, Gemini, or open-source alternatives) via APIs or self-hosted inference.
Hands-on experience with agentic frameworks such as LangChain, LlamaIndex, or AutoGen to build multi-step, tool-augmented AI workflows.
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 $212,000 and $318,400, 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