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Machine Learning Data Associate Jobs in California

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Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide ...

Rule14

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Data Scientist Machine Learning

Santa Monica, CA · On-site

$65K - $85K/yr

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

Handshake

Machine Learning Engineer I

San Francisco, CA · On-site

$151K - $189K/yr

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work ... Machine Learning is at the heart of Handshake's mission to democratize access to opportunity. Every ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$112.10K - $154K/yr

Perform data preprocessing, feature engineering, model evaluation, and validation. * Collaborate ... Associate II $165,000 - $195,000 Disclaimer: This in no way states or implies that these are the ...

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

As of May 30, 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 are the key skills and qualifications needed to thrive as a Machine Learning Data Associate, and why are they important?

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 are Machine Learning Data Associates?

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 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.

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
Machine Learning Intern

Machine Learning Intern

EarnIn

Mountain View, CA • Hybrid

$40/hr

Other

Posted 21 days ago

Job description

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide a detailed formulation, extensive experimentation, and to transform ML models into high-performance production-level code, including not only implementing sophisticated machine learning algorithms but also robustness monitoring and system logging/alarming. 

 We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with experienced professionals, gain valuable experience in the fintech industry, and realize business and social impact. This role requires hybrid work from our Mountain View office, with 2 days a week in person. This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program. We are unable to provide visa sponsorship or immigration support for this position.  

WHAT YOU'LL DO 

  • Train and fine-tune large-scale Foundation Models to support various fintech product use cases
  • Work with a large dataset, including structured and unstructured data
  • Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades
  • Gain hands-on experience with a wide array of technologies, including PyTorch, AWS, Kafka, Databricks, etc

WHAT WE'RE LOOKING FOR

  • Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field
  • Located in Mountain View, or have the ability to relocate there, for the duration of the internship 
  • Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large-scale models, Sequence Transformer models 
  • Interest in multimodal or multitask learning across structured, sequential, and behavioral data
  • Familiarity with AI tools, harness engineering, agentic workflow, etc.
  • Hands-on programming experience in Python and ML frameworks such as PyTorch
  • Equipped with good verbal and written communication skills
  • A background demonstrating strong problem-solving skills
  • Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion

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