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Machine Learning Data Associate Jobs (NOW HIRING)

Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related ... discipline. Direct relevant military experience will also be considered. Minimum of 3 years related ...

Principal Machine Learning & Data Engineer

$138K - $185K/yr

About the job Twilio's next L5 Machine Learning & Data Engineer to lead the design, build, and operation of the internal ML-and-data platform that powers every customer interaction. You will ...

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Machine Learning Data Associate information

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

As of Jun 19, 2026, the average hourly pay for machine learning data associate in the United States is $18.74, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $19.95 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.

What is the salary of ML data associate?

The salary of a Machine Learning Data Associate typically ranges from $40,000 to $70,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced professionals with specialized skills in data annotation and tools like Python or SQL can earn higher salaries.

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.

Is ML 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. Job satisfaction depends on individual interests and career goals in technology and data fields.

How much do ML data associates make in the US?

Machine Learning Data Associates in the US typically earn between $35,000 and $60,000 annually, depending on experience, location, and employer. Entry-level positions may start lower, while those with specialized skills in data annotation, labeling, or familiarity with tools like Labelbox or CVAT can command higher salaries.

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 does a machine learning data associate do?

A machine learning data associate is responsible for collecting, cleaning, and organizing data used to train machine learning models. They ensure data quality and consistency, often using tools like SQL, Python, or data annotation platforms, to support accurate model development and deployment.
What cities are hiring for Machine Learning Data Associate jobs? Cities with the most Machine Learning Data Associate job openings:
What states have the most Machine Learning Data Associate jobs? States with the most job openings for Machine Learning Data Associate jobs include:
Infographic showing various Machine Learning Data Associate job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 1% As Needed, 69% Full Time, 25% Part Time, 1% Temporary, and 3% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $38,974 per year, or $18.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

ENSCO, Inc.

Melbourne, FL โ€ข On-site

Other

Posted 28 days ago


Job description

ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets. ย Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters. ย The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions. ย Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments.
ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security. ย A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
ย 

Qualifications Required:
ย  ย  ย  ย  Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline. ย Direct relevant military experience will also be considered.
ย  ย  ย  ย  Minimum of 3 years related industry experience in machine learning, data science, and analytics.
ย  ย  ย  ย  Proven track record of successful data science and algorithm implementation.
ย  ย  ย  ย  Provide mentorship to junior ML engineers.
ย  ย  ย  ย  A self-starter with excellent oral and written communication skills.
ย  ย  ย  ย  Experience navigating and programming within the Linux environment.
ย  ย  ย  ย  Experience working with structured and unstructured databases.
ย  ย  ย  ย  Advanced proficiency with data science languages (e.g. Python, Matlab,)
ย  ย  ย  ย  Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet).
ย  ย  ย  ย  Experience working with large data sets and ability to extract relevant information from data sets.
ย  ย  ย  ย  ย The ability to obtain and maintain a US security clearance is required for this position, for which you must be a U.S. Citizen

Qualifications Desired:
ย  ย  ย  ย  Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent.
ย  ย  ย  ย  Experience with ML/DL algorithms extracting signal from noise.
ย  ย  ย  ย  Past experience being able to develop solutions using disparate data sets through ML techniques.
ย  ย  ย  ย  DevOps experience involving CI/CD pipelines to build and deploy.
ย  ย  ย  ย  Experience working with container orchestration technologies (e.g. Docker/Kubernetes).
ย  ย  ย  ย  An Active TS/SCI clearance.
ย 

Work Location Type: Hybrid
Required Certifications: None
U.S. Citizenship Required: Yes
Security Clearance Required: Ability to obtain
Employment Type: Regular Full-time
Background Check Type: ย 7 Year Pre-Employment
Drug Screen Required: None
Position Contingent Upon Contract Award: Yes