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Machine Learning Data Associate Jobs in Torrance, CA

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Crowe LLP

Machine Learning Intern

Los Angeles, CA · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

Develop deep learning models for prototyping and production purposes according to product feature ... Provide insights to data collection and annotation and collaborate with the data team for in-house ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA

Develop deep learning models for prototyping and production purposes according to product feature ... Provide insights to data collection and annotation and collaborate with the data team for in-house ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Torrance, CA

Machine Learning Data Associate information

See Torrance, CA salary details

$10

$19

$32

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

As of Sep 13, 2026, the average hourly pay for machine learning data associate in Torrance, CA is $19.57, according to ZipRecruiter salary data. Most workers in this role earn between $16.06 and $20.82 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 Torrance, CA are hiring for Machine Learning Data Associate jobs?

Cities near Torrance, 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 Torrance, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $40,697 per year, or $19.6 per hour.

Machine Learning Engineer

Huntington Beach, CA • On-site

Layup Parts
See more jobs at Layup Partsexternal

$120K - $185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 11 days ago

Job description

At Layup Parts, we're developing the technology that will build the future.
We're a manufacturing technology company replacing months of lead time with days, using proprietary software, automation, and advanced manufacturing systems built for speed. Our customers are inventing what's next, in aerospace, defense, robotics, and beyond. To keep up with them, manufacturing has to change. That's what we're building.
We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given design, and extracting structured data out of existing documentation. We're looking for someone who has trained custom models on large, parameter-rich datasets, ideally with a geometric or spatial component, and who is energized by problems in that space specifically.
What You'll Do
  • Train and iterate on custom ML models using Layup's internal manufacturing and design data
  • Build models that estimate cost and predict design complexity or manufacturing difficulty from part geometry
  • Develop models that generate or assist in generating new designs based on historical design data
  • Build pipelines to extract structured data (specs, dimensions, material callouts, etc.) from existing engineering documents and drawings
  • Evaluate and select modeling approaches suited to geometric, spatial, and other structured data, rather than text-based problems
  • Work closely with engineering and manufacturing teams to source, clean, and label internal datasets
  • Own model performance end-to-end, from data pipeline through training, evaluation, and deployment into internal tools
  • Continuously identify new opportunities where custom models could improve design, estimation, or manufacturing workflows

What We're Looking For
  • Experience training custom models beyond basic labeling or fine-tuning workflows
  • Experience with advanced object detection at minimum; data classification experience is a strong plus
  • Experience with geometry-based modeling is highly preferred
  • Experience working with large, parameter-rich datasets
  • Strongest fit is someone whose background is in structured, spatial, or geometric data problems rather than natural language or LLM-centric work

Bonus Points
  • Experience training geometry-specific models
  • CAD experience
  • Manufacturing experience

$120,000 - $185,000 a year
Final compensation is based on your experience, skills, and what you bring to the table.
  • Full Benefits Package: Medical, dental, and vision coverage, short- and long-term disability insurance, company-paid life insurance
  • Equity Option Grants
  • 401k plan
  • Paid Time Off: Unlimited PTO + 9 Federal Holidays

Equal Opportunity
Layup is an equal-opportunity employer. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws, including the CA Fair Chance Initiative for Hiring Ordinance.
ITAR Requirements
To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (aka green card holder), (iii) Refugee under 8 U.S.C. § 1157, or (iv) Asylee under 8 U.S.C. § 1158, or be eligible to obtain the required authorizations from the U.S. Department of State. Learn more about the ITAR here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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