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Machine Learning Qa Jobs in California (NOW HIRING)

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$100K - $150K/yr

The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ... Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation * Publish ...

Karius

Quality Assurance Associate

Redwood City, CA · On-site

The Quality Assurance Associate must demonstrate a high level of individual responsibility and ... machine learning. The company's platform is already delivering unprecedented insights into the ...

StartX

Quality Assurance Associate

Redwood City, CA · On-site

The Quality Assurance Associate must demonstrate a high level of individual responsibility and ... machine learning. The company's platform is already delivering unprecedented insights into the ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$216K - $324K/yr

The Machine Learning Platform Technology team is building groundbreaking technology for search ... quality data tooling that improves data velocity, reliability, and scalability Apply expertise in ...

Western CNC

Be Seen First

Quality Assurance Manager

Vista, CA · On-site

$90K - $125K/yr

We are a fast pace, large CNC machine shop looking for a Quality Assurance Manager 25+ Fanuc controlled vertical mills 16+ controlled horizontal mills 10+ CNC lathes with Fanuc controls 10+ Brother ...

Poshmark

Sr. Engineer, Machine Learning

Redwood City, CA · On-site

$127K - $175K/yr

The Machine Learning team is a central player in the Poshmark organization. Our mission is to build ... Collaborate across teams such as DS, QA, Infra and other engineering teams to productionize ML ...

Alcon3Pl

Machine Operator / QA - 1st Shift

Hayward, CA

$24 - $25/hr

Machine Operator / QA - 1st Shift Lobos Staffing is hiring an experienced Machine Operator with a strong Quality Assurance background. Schedule: Monday-Friday, 6:00 AM-2:30 PM Pay: $24-$25/hour ...

Alcon3Pl

Machine Operator / QA - 1st Shift

Hayward, CA

$24 - $25/hr

Machine Operator / QA - 1st Shift Lobos Staffing is hiring an experienced Machine Operator with a strong Quality Assurance background. Schedule: Monday-Friday, 6:00 AM-2:30 PM Pay: $24-$25/hour ...

Apple

ML Data QA Lead, MLO

Cupertino, CA · On-site

Do you believe Machine Learning and AI can change how people experience technology? We truly ... We are looking for a talented individual to drive data quality assurance for the ML features we ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only ... You will collaborate closely with partners in production, process, controls, and quality to deliver ...

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Machine Learning Qa information

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How much do machine learning qa jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for machine learning qa in California is $44.29, according to ZipRecruiter salary data. Most workers in this role earn between $36.06 and $53.85 per hour, depending on experience, location, and employer.

What is a machine learning QA?

A Machine Learning QA (Quality Assurance) professional is responsible for testing and validating machine learning models to ensure accuracy, reliability, and performance. They design test cases, create automated testing pipelines, and identify biases or errors in datasets and model outputs. Their role bridges software testing and data science, ensuring that ML systems function correctly in production.

What does a machine learning QA do?

A Machine Learning QA professional is primarily responsible for designing, implementing, and executing test plans to ensure the quality and performance of machine learning models and their integration into software products. This often involves developing automated tests, validating dataset integrity, monitoring model outputs, and collaborating closely with data scientists and developers to resolve issues. Additionally, you may participate in code reviews, maintain testing documentation, and contribute to continuous improvement of testing processes. The role is collaborative and requires balancing technical rigor with practical problem-solving to help deliver robust AI-powered applications.

What skills and qualifications are needed for a machine learning QA?

Success as a Machine Learning QA requires a solid understanding of software testing principles, machine learning concepts, and programming skills, typically supported by a degree in computer science or a related field. Familiarity with tools like Python, TensorFlow or PyTorch, and QA automation frameworks, as well as relevant certifications in software testing or ML, are often advantageous. Strong analytical thinking, attention to detail, and effective communication are standout soft skills in this role. These competencies are essential for ensuring machine learning models function as intended, meet quality standards, and integrate smoothly into production environments.

What are popular job titles related to Machine Learning Qa jobs in California?

For Machine Learning Qa jobs in California, the most frequently searched job titles are:

What job categories do people searching Machine Learning Qa jobs in California look for?

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Machine Learning Qa jobs near you
Infographic showing various Machine Learning Qa job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $92,115 per year, or $44.3 per hour.

Machine Learning Engineer

San Francisco, CA • On-site

Human Archive
See more jobs at Human Archiveexternal

Other

Re-posted 20 days ago

Job description

About Human Archive

Human Archive is a research lab focused on modeling human embodied intelligence.

Humans are the most sophisticated biological systems we have ever observed, yet we still do not fully understand ourselves. Research into human physical intelligence — including the human hand, proprioception, and vision — remains largely unsolved. Our mission is to recover human embodied intelligence as a learned model. To achieve this, we build custom hardware products, deploy them globally at scale, and publish research. Today, our data is used for robotics and world modeling, but the broader opportunity is advancing scientific research into intelligence itself.

Founded by Stanford and UC Berkeley researchers, we are lean, deeply technical, and operate at extreme speed, taking on unglamorous and conventionally impossible problems that directly unlock step-function gains in model capability.

The deployment of capable humanoids at scale will permanently redefine human labor. Undesirable physical work will disappear, and human effort will shift toward a new era of abundant creativity.

We are building the infrastructure to accelerate that transition by assembling the Human Archive mafia. You will own meaningful systems from day one and see your work directly impact model capabilities. This is a once-in-a-generation inflection point. If you want to help reshape physical labor and work on problems that matter at civilizational scale, join us.

The Opportunity

As a Machine Learning Engineer, you’ll work on multimodal perception, VLA training, robotics post-training, and downstream policy evaluation. This is a hands-on role at the intersection of applied machine learning, data infrastructure, and robotics, where your work directly shapes how data is collected, validated, annotated, and evaluated.

You’ll help close the loop between research and data collection by fine-tuning VLAs on downstream policy performance and building post-training and reinforcement learning systems around real-world robotics tasks. You’ll be expected to make architectural decisions, own projects end-to-end, and operate in highly ambiguous research environments given the novelty and scale of our multimodal datasets.

Your work will help shape how frontier labs and leading robotics companies train their models, transforming physical labor markets and economies while contributing to broader research into human embodied intelligence.

What You’ll Do

  • Build systems for multimodal perception, annotation, dataset QA, and robotics evaluation

  • Publish research on multimodal data by fine-tuning and evaluating VLA models on downstream robotics tasks and policy performance

  • Build post-training and reinforcement learning systems around robotics failure modes and corrective demonstrations

  • Work across video understanding, tracking, pose estimation, temporal modeling, and multimodal alignment

  • Develop tooling for benchmarking, observability, and temporal efficiency

  • Prototype quickly, ship rapidly, and iterate from real-world robotics deployments and research feedback

What We’re Looking For

  • Passionate, mission-driven individuals who have demonstrated exceptional ownership in previous work

  • Engineers who want their work to directly impact the next frontier of physical AGI

  • Strong ML engineering fundamentals across robotics, computer vision, and perception systems

  • Experience with video understanding, tracking, pose estimation, robotics, or real-world sensor systems

  • Strong technical intuition and ability to move quickly in ambiguous research environments

  • Published research or production experience in robotics, embodied AI, reinforcement learning, motion capture, or vision systems is a strong plus

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