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Machine Learning Data Associate Jobs in Texas (NOW HIRING)

RealmOne

Data Scientist 3

San Antonio, TX · On-site

Required : • Bachelor's degree and 10 years' relevant experience OR Associate's degree plus 12 ... Machine Learning, Data Science, Operations Research, or Computer Science. • A degree in a related ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... data warehouse platform using the Snowpark framework Develop novel solutions using knowledge of the latest artificial intelligence/machine learning/natural language processing techniques and rigorous ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Texas

Machine Learning Data Associate information

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$28

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

As of Aug 20, 2026, the average hourly pay for machine learning data associate in Texas is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $18.61 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 in Texas are hiring for Machine Learning Data Associate jobs?

Cities in Texas 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 Texas as of August 2026, with employment types broken down into 67% Full Time, 11% Part Time, 11% Contract, and 11% Nights. Highlights an 100% In-person job distribution, with an average salary of $36,310 per year, or $17.5 per hour.

Machine Learning Engineer - Strategic Data Solutions

Apple

Austin, TX

$113K - $136K/yr

Full-time

Re-posted 14 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that’s constantly learning and having fun while solving tough business problems? We’d love to talk to you if you do!
At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
As an SDS MLE, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions
• Collaborate with technical partners to implement robust real-time and batch decisioning in production
• Create reporting and monitor decisioning quality to maintain operational and business metric health
• Investigate trends, assess threat impact, and respond with agile logic changes
• Communicate with stakeholders with varying technical backgrounds and business priorities about your work
• Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities
Preferred Qualifications
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions
Team-oriented skills and values to facilitate effective collaboration with business and technical partners
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor’s degree with equivalent experience
Practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions
Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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