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Machine Learning Qa Jobs in California (NOW HIRING)

Machine Learning Engineer (Full time) JOB DUTIES: The Machine Learning Engineer will design ... Design and develop internal software tools and backend services that support data quality, enable ...

Machine Learning Engineer The Opportunity Join Adobe and be at the forefront of driving digital ... Engage in code reviews and contribute to maintaining high-quality standards in software development

Machine Learning EngineerThe Opportunity Join Adobe and be at the forefront of driving digital ... Engage in code reviews and contribute to maintaining high-quality standards in software development

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 ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ... Write clean, well-documented, and production-quality Python code. * Communicate findings, results ...

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... quality metrics are achieved * Implement and manage security protocols such as training, code ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility ... You will collaborate closely with partners in production, process, controls, and quality to deliver ...

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive ... Familiarity with LLM evaluation practices including output quality assessment, hallucination ...

OpenReq is focused on innovative AI chip technology, and they are seeking a Machine Learning ... Responsibilities : • Combine multi-agent with RAG to improve the quality of QA • Evaluate new ...

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... quality metrics are achieved * Implement and manage security protocols such as training, code ...

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Machine Learning Qa information

See California salary details

$14

$44

$63

How much do machine learning qa jobs pay per hour?

As of Jul 8, 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.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and deploying complex models, making complete replacement unlikely in the near term. MLEs also need skills in programming, data analysis, and understanding of algorithms to adapt to evolving AI technologies.

What is a Machine Learning QA job?

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.

Is AI taking over QA jobs?

AI and automation are increasingly used in quality assurance roles, especially for repetitive testing tasks, but they complement rather than replace QA jobs. Skilled QA professionals who focus on test design, analysis, and complex problem-solving remain essential, and knowledge of automation tools like Selenium or TestComplete enhances employability.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and working at large tech companies or in specialized industries can earn salaries around $500,000 annually. Compensation often includes base salary, bonuses, and stock options, especially in high-demand markets.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior machine learning engineer or AI director, with a compensation package that includes salary, bonuses, and stock options reaching or exceeding that amount annually. These roles often require advanced skills in machine learning, deep learning, data analysis, and experience with tools like TensorFlow or PyTorch, along with a strong educational background and industry experience.

What are the typical daily responsibilities of a Machine Learning QA professional?

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

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? The top searched job categories for Machine Learning Qa jobs in California are:
What cities in California are hiring for Machine Learning Qa jobs? Cities in California with the most Machine Learning Qa job openings:
Machine Learning Engineer

Machine Learning Engineer

Alt

San Francisco, CA • On-site, Remote

$196K/yr

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

REFERRALS: The below position is eligible for employee incentives provided pursuant to Alt Platform Inc.'s referrals policy, which is described in detail at https://app.notion.com/p/altxyz/Hiring-Referral-program-29d859d114314e39886ae51c9fb1bdf9?source=copy_link

EMPLOYER NAME: Alt Platform Inc.

JOB TITLE: Machine Learning Engineer (Full time)

JOB DUTIES: The Machine Learning Engineer will design, develop, deploy, and maintain advanced machine learning models and data analysis systems to support specialized domain modeling and proprietary feature engineering. The person in this role will analyze structured and unstructured datasets, perform applied experimentation, develop production-grade machine learning pipelines, optimize modeling infrastructure, and collaborate across business and engineering teams to translate business needs into scalable data-driven solutions. The Machine Learning Engineer will be primarily responsible for the following duties:

  • Conduct applied research and experimentation to design, train, evaluate, and refine machine learning models, including performing feature engineering, selecting modeling techniques, validating model performance, and documenting analytical methods.
  • Develop, test, and deploy production machine learning systems by managing the complete MLOps lifecycle, including experiment tracking, model versioning, containerization, orchestration of automated workflows, and monitoring of model performance in production environments.
  • Maintain and optimize machine learning infrastructure to support training, inference, and data processing workflows, including configuring cloud compute environments, tuning distributed computation jobs, and improving system efficiency and scalability.
  • Collaborate with business stakeholders to translate analytical requirements into quantifiable modeling objectives, define evaluation criteria, validate assumptions with data, and communicate analytical findings and modeling results.
  • Design, prepare, and review technical documentation, including model design specifications, architecture diagrams, data-flow documentation, and systems integration requirements to support maintainability and long-term scalability.
  • Develop AI-driven automation solutions using Large Language Models to streamline internal workflows, design LLM-based agentic processes, validate automated outputs, and measure accuracy and efficiency improvements.
  • Design and develop internal software tools and backend services that support data quality, enable analytical workflows, expose model insights to internal teams, and integrate with organizational data systems and APIs.

No travel is required.

Fully remote position (100%) from anywhere in U.S. reporting to HQ in  San Francisco, CA 

JOB REQUIREMENTS: Master's degree (or foreign equivalent) in data science, economics, mathematics or computer science and 1 year of experience in any occupations in which required experiences were acquired (may be pre-Master's).  Professional experiences must include:

  • 1 year of experience designing, training, and evaluating machine learning models using Python-based data science libraries, including experience performing feature engineering and developing predictive and descriptive models using tools such as scikit-learn and pandas.
  • Experience using machine-learning lifecycle tools, including MLflow (or similar platforms) for experiment tracking, reproducible training workflows, and model versioning.
  • Experience using Docker for containerization to package machine learning pipelines and ensure reproducible deployment environments.
  • 1 year of experience orchestrating data processing and machine learning workflows, including scheduling, monitoring, and managing dependencies using Apache Airflow.
  • 1 year of experience using CI/CD tools to automate model training, testing, and deployment processes.
  • 1 year of experience configuring and optimizing cloud compute environments to support training, inference, and large-scale data processing tasks.
  • 1 year of experience developing AI-driven automation workflows using language models, including integrating language-based model components into analytical or operational processes.
  • Experience developing backend services and APIs using FastAPI, REST, or GraphQL to support data access, model serving, and analytical tooling.
  • 1 year of experience working with SQL databases, including PostgreSQL, and cloud data platforms (e.g., Snowflake), including writing analytical queries and implementing data-quality validation workflows.
  • Experience using distributed data-processing tools, including Spark, for large-scale data transformation and feature-engineering operations.

SALARY OFFERED: From $196,776 per year

JOB LOCATION: San Francisco, CA

TO APPLY SEND RESUME TO: Eryn@alt.xyz (write "Machine Learning Engineer" in subject line)