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Machine Learning Data Associate Jobs in Santa Clara, CA

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

The Machine Learning Platform Technology team is building groundbreaking technology for search ... Our infrastructure and research for data curation form the backbone of Apple Intelligence. It ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$216K - $324K/yr

The Machine Learning Platform Technology team is building groundbreaking technology for search ... Our infrastructure and research for data curation form the backbone of Apple Intelligence. It ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Santa Clara, CA

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 Santa Clara, CA is $22.01, according to ZipRecruiter salary data. Most workers in this role earn between $18.08 and $23.41 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 near Santa Clara, CA are hiring for Machine Learning Data Associate jobs?

Cities near Santa Clara, CA 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 Santa Clara, CA as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $45,773 per year, or $22 per hour.

Machine Learning & Data Engineer, Vehicle Modeling

Sunnyvale, CA • On-site

42dot
See more jobs at 42dotexternal

$136K - $163K/yr

Other

Posted 8 days ago

Job description

We are looking for the best About Us

42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles.

We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.

About the Role

We are building next-generation vehicle modeling and data technology at 42dot by combining physics-based models, machine learning, simulation, and large-scale vehicle data.

As a Machine Learning & Data Engineer, Vehicle Modeling, you will develop ML and data infrastructure that improves vehicle models and supports broader vehicle intelligence and autonomous driving development. You will work across vehicle telemetry, simulation, test data, fleet data, and cloud platforms to build scalable systems for model development, evaluation, and continuous improvement.

A core focus of this role is using real-world vehicle data to identify model performance gaps and improve models through calibration, parameter estimation, machine learning, and hybrid physics-and-data approaches. You may develop ML models that complement physics-based models, estimate model parameters under different vehicle states and operating conditions, or improve predictions where physical models alone are insufficient.

You will also help build the data and cloud infrastructure needed to ingest, clean, organize, process, and evaluate large-scale vehicle datasets, supporting modeling, simulation, vehicle intelligence, and autonomous driving workflows. This role sits at the intersection of machine learning, data engineering, physical system modeling, simulation, and vehicle software.

Responsibilities

  • Develop machine learning and hybrid physics-data approaches to improve vehicle and component model accuracy.

  • Develop methods for model calibration, parameter estimation, adaptive modeling, and data-driven model improvement across different vehicle states and operating conditions.

  • Build scalable workflows for comparing model predictions with test, simulation, and real-world vehicle data and identifying opportunities for model improvement.

  • Build pipelines for ingesting, cleaning, synchronizing, transforming, storing, and accessing large-scale vehicle telemetry and time-series data.

  • Develop cloud-based infrastructure for data processing, model training, simulation, evaluation, and validation.

  • Build tools and workflows for dataset management, model evaluation, experiment tracking, and reproducible model development.

  • Support data processing, model evaluation, and analysis workflows used by vehicle intelligence

Interview Process

  • Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring

  • The screening procedures may vary depending on the position, schedule, or other circumstances.

    You will be individually notified of the screening schedule and results via the email address provided in your application.

Additional Information

  • In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.

  • All documents must be submitted in PDF format and under 30MB in size.

  • If you experience issues uploading your resume, please send it along with the job posting URL to recruit@42dot.ai.

  • We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.

  • Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).

  • 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement

  • 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

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