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Entry Level Machine Learning Data Annotation Jobs in Los Angeles, CA

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from ...

Machine Learning Engineer II

Los Angeles, CA · On-site +1

$145K - $165K/yr

You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from ...

Machine Learning Engineer II

Los Angeles, CA · On-site +1

$105K - $143K/yr

You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from ...

Develop encoding and embedding techniques that allow consistent comparison across multiple data ... machine learning roles through internships, academic labs, or early career positions. * Strong ...

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 ...

Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Build and maintain infrastructure for data ingestion from surgical robotic systems, annotation ... Familiarity with machine learning data lifecycle concepts (dataset versioning, data drift ...

Showing results 21-40

Entry Level Machine Learning Data Annotation information

See Los Angeles, CA salary details

$12

$21

$33

How much do entry level machine learning data annotation jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for entry level machine learning data annotation in Los Angeles, CA is $21.81, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $23.56 per hour, depending on experience, location, and employer.

What is the difference between Entry Level Machine Learning Data Annotation vs Entry Level Data Labeling Specialist?

AspectEntry Level Machine Learning Data AnnotationEntry Level Data Labeling Specialist
CredentialsBasic understanding of data annotation tools, no formal certification requiredSimilar; often no formal certification needed
Work EnvironmentRemote or on-site, working with AI teams and datasetsRemote or on-site, focusing on labeling data for AI/ML projects
Industry UsagePrimarily in AI, machine learning, and data science companiesUsed across tech, automotive, healthcare, and other industries
Search & Comparison IntentCommonly compared for entry-level roles in AI data prepOften compared as a similar entry-level data labeling role

Both roles involve preparing data for machine learning models, with similar entry-level requirements. The main difference lies in terminology and specific job focus, but they often overlap in skills and work environment.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Los Angeles, CA? The most popular types of Machine Learning Data Annotation jobs in Los Angeles, CA are:
What are popular job titles related to Entry Level Machine Learning Data Annotation jobs in Los Angeles, CA? For Entry Level Machine Learning Data Annotation jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Data Annotation jobs in Los Angeles, CA look for? The top searched job categories for Entry Level Machine Learning Data Annotation jobs in Los Angeles, CA are:
Infographic showing various Entry Level Machine Learning Data Annotation job openings in Los Angeles, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $45,362 per year, or $21.8 per hour.

Machine Learning User Research Scientist (Ph.D. required)

Exponent

Los Angeles, CA • On-site

Full-time

Re-posted 25 days ago


Job description

Job Summary:
Exponent is a premium engineering and scientific consulting firm dedicated to solving unique challenges for clients. They are seeking a Ph.D. level Machine Learning User Research Scientist to contribute to global data collection efforts and optimize programs for the consumer electronics industry.
Responsibilities:
• Supporting a range of consulting activities related to large-scale local and global programs to build custom datasets for machine learning algorithms including protocol development, data collection, data management, and analysis
• Providing operational support for prototype hardware and software systems including system validation and troubleshooting
• Actively solving technical and logistical problems in a fast-paced environment
• Creating and leading ad hoc interdisciplinary teams comprised of consultants from Data Sciences, Human Factors, Health Sciences, and Engineering Sciences
• Developing data analysis and visualization tools related to project management, demographics, and human-centered data
• Developing and maintaining client relationships
Qualifications:
Required:
• Ph.D. in Electrical Engineering, Computer Engineering, Physiology, Human Factors, or a related engineering/scientific field (such as Applied Mathematics, Computer Science, Cognitive Science, Applied Physics, Industrial Engineering, Mechanical Engineering, Civil Engineering, or Robotics)
• Ability to take an ambiguous question, use data to draw insights, and convey the results to a wide range of audiences
• Demonstrated experience and expertise in one or more of the following areas: Advanced sensing technology, Networking data analysis and visualization, Designing and executing user research studies with human subjects, using appropriate quantitative and qualitative methods to produce strategic and actionable insights that inform design and development, Experience in programming or scripting languages like Python, Shell, Java, Perl, MATLAB, Experience in instrumentation, data acquisition, and /or data processing, Operations optimization, Machine learning data set design or optimization, Dynamic system modeling and control
• Experience with human subjects research or direct collection of large experimental data sets to support the development of machine learning or artificial intelligence algorithms
• The desire to work with a diverse set of clients and engage in work outside of the traditional data science field
• Strong practical engineering ability combined with leadership and project management skills
• Excellent verbal and written communication skills
• Ability to work independently and in multidisciplinary teams
• Ability to travel to a variety of global locations to support project work (up to 40% travel)
• Presently legally authorized to work in the United States; no immigration sponsorship or processing required
Company:
With over 90 scientific and engineering disciplines, Exponent’s staff of approximately 900, located in 20 offices throughout the USA Founded in 1967, the company is headquartered in Menlo Park, USA, with a team of 1001-5000 employees. The company is currently Late Stage.