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Machine Learning Data Associate Jobs in California

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$100K - $150K/yr

Today, our data is used for robotics and world modeling, but the broader opportunity is advancing ... The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ...

Syntricate Technologies

Machine Learning

Cupertino, CA · On-site

The role involves deploying client models, managing data pipelines, and building chatbots using ... machine learning principles, especially in the context of LLMs. • Experience building chatbots ...

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

D. in Computer Science, Data Science, or a related field • Strong programming skills in Python or R • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) • Knowledge of ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site

We're seeking an outstanding ML Engineer to join our data team and help build out best-in-class machine learning solutions on our platform, powering innovative solutions in marketing & sales and ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in California

Machine Learning Data Associate information

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How much do machine learning data associate jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for machine learning data associate in California is $18.49, according to ZipRecruiter salary data. Most workers in this role earn between $15.19 and $19.71 per hour, depending on experience, location, and employer.

What is a machine learning data associate?

Machine Learning Data Associates are professionals who support the development of machine learning models by preparing, labeling, and validating data sets. Their work ensures that data used for training algorithms is accurate, consistent, and properly annotated. They may also assist with data cleaning, quality checks, and sometimes basic data analysis tasks. This role is crucial in industries where high-quality labeled data is essential for building effective AI systems.

What are the key skills and qualifications needed to thrive as a machine learning data associate?

To thrive as a Machine Learning Data Associate, you need strong analytical skills, attention to detail, and a basic understanding of data annotation and labeling processes, often supported by a degree in computer science or a related field. Familiarity with data management tools, annotation platforms, and sometimes scripting languages like Python is typically required. Strong communication, collaboration, and problem-solving abilities help you work efficiently with data science teams and ensure high-quality outcomes. These skills and qualities are crucial for producing accurate datasets that directly impact the effectiveness of machine learning models.

How does a machine learning data associate typically collaborate with data scientists and engineers within a project team?

As a Machine Learning Data Associate, you play a vital role in supporting data scientists and engineers by annotating, cleaning, and organizing large datasets to ensure high data quality. You'll frequently communicate with team members to clarify labeling guidelines, provide feedback on data inconsistencies, and report any edge cases encountered during annotation. This collaboration ensures that the datasets used for training machine learning models are accurate and comprehensive, directly impacting the success of the project. Expect regular team meetings and ongoing feedback loops to maintain alignment with evolving project requirements.

What is the difference between Machine Learning Data Associate vs Data Analyst?

AspectMachine Learning Data AssociateData Analyst
Required SkillsData cleaning, labeling, basic programming, understanding of ML workflowsData interpretation, visualization, statistical analysis
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, marketing, healthcare sectors
Common CertificationsData Science certifications, Python, SQLExcel, Tableau, SQL certifications

The main difference is that Machine Learning Data Associates focus on preparing and labeling data specifically for machine learning models, while Data Analysts interpret data to generate insights for business decisions. Both roles require strong data skills and often overlap, but their primary objectives and work environments differ.

How do I become a machine learning data associate?

To become a machine learning data associate, candidates typically need a high school diploma or equivalent, with some roles preferring a bachelor's degree in computer science, data science, or related fields. Relevant skills include data annotation, understanding of machine learning concepts, and proficiency with tools like Excel, SQL, or data labeling platforms. Gaining experience through internships or certifications can improve job prospects in this field.

Is a Machine Learning Data Associate a good job?

A Machine Learning Data Associate role involves preparing and managing data for machine learning models, often requiring skills in data cleaning, annotation, and familiarity with tools like Python or SQL. It can be a good entry-level position for those interested in AI and data science, offering opportunities to develop technical skills and gain industry experience. Compensation and job satisfaction vary depending on the employer and location, but it generally provides a solid foundation for a career in machine learning or data analysis.

What cities in California are hiring for Machine Learning Data Associate jobs?

Cities in California with the most Machine Learning Data Associate job openings:

Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $38,464 per year, or $18.5 per hour.

Machine Learning Engineer

Sunnyvale, CA • On-site

Institute of Foundation Models
See more jobs at Institute of Foundation Modelsexternal

$150K - $450K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted yesterday

Key responsibilities

  • Collaborate with research teams to understand and integrate technologies into the codebase.

  • Develop and implement systems to support the lifecycle of machine learning models, especially foundation models.

  • Review code developed by others, provide feedback, and contribute to documentation and educational content.

Job description

About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.



The Role
As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world challenges, pushing the boundaries of artificial intelligence research. You will collaborate with cross-functional teams to deploy scalable solutions, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide.
Key Responsibilites
  • Collaborate with Research teams to understand technologies, adapting and integrating them into codebase.
  • Develop and implement systems to support the lifecycle of machine learning models, such as data preprocessing, pre-training, post-training, evaluation and so on, especially foundation models.
  • Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
  • Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
  • Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  • Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  • Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation.
  • Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives.
Academic Qualifications
  • Minimum: Bachelor’s degree or equivalent practical experience. 
  • Preferred: Master's degree or PhD in Computer Science or related technical field.
 
Professional Experience - Minimum
  • 3 years of experience in software engineering, including experience with Machine Learning (ML) models, ML infrastructure, Natural Language Processing or Computer Vision.
  • 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree in an industry setting.
  • 2 years of experience with data structures or algorithms in either an academic or industry setting.
  • 2 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
  • Excellent problem-solving and troubleshooting skills to address complex technical challenges.
  • Effective communication and collaboration skills to work with cross functional teams.
Professional Experience - Preferred
  • 2 years of experience with improving performance during large scale data processing
  • Hands-on experience with LLM algorithms, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF).
  • Excellent data analysis skills.
Visa Sponsorship
This position is eligible for visa sponsorship.

Benefits Include
*Comprehensive medical, dental, and vision benefits 
 *Bonus
*401K Plan
*Generous paid time off, sick leave and holidays
*Paid Parental Leave
*Employee Assistance Program
*Life insurance and disability