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Machine Learning Testing Jobs in California (NOW HIRING)

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... testing, and deployment in production * Drive delivery for our product milestones, continually ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

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 ...

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... testing, and deployment in production * Drive delivery for our product milestones, continually ...

... testing workflows. Minimum Qualifications * 4+ years of related experience building high throughput scalable applications or building machine learning models. * Proficiency in one or more object ...

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... testing, and deployment in production * Drive delivery for our product milestones, continually ...

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and ... A/B testing. * Have built backend production services on cloud environments like AWS, using ...

Machine Learning Engineer

San Francisco, CA · On-site

$205K - $316.40K/yr

Machine Learning Engineer At Quizlet, our mission is to help every learner achieve their outcomes ... Establish evaluation frameworks connecting offline metrics to online impact (A/B testing) * Improve ...

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Machine Learning Testing information

See California salary details

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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

RZR Global Inc.

San Francisco, CA • On-site

Full-time

Posted 12 days ago


Job description

Who are we?RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
The role?
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
What will you do?
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Analyze the impact of integrating new data sources and features into our models.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • Document experiments, assumptions, and outcomes; maintain reproducibility
What are we looking for?
  • Bachelor's degree in Mathematics, Physics, Computer Science, or a related technical field.
  • At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
Nice-to-Have
  • Familiarity with system programming languages including C++ and Rust is a plus.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.