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Machine Learning Data Associate Jobs in Philadelphia, PA

Varsity Tutors

Machine Learning Tutor

Trenton, NJ · Remote

$40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

BE Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role is focused on building the ...

Varsity Tutors

Machine Learning Tutor

Chester, PA · Remote

$40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

asrcfh

Expert Machine Learning Engineer

Moorestown, NJ · On-site

Responsibilities: • Develops, researches, and applies machine learning, deep learning, visual artificial intelligence algorithms and methods to data sets to produce models to be deployed in an ...

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All JobsMachine Learning Data Associate JobsMachine Learning Data Associate Jobs in Philadelphia, PA

Machine Learning Data Associate information

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

As of Sep 12, 2026, the average hourly pay for machine learning data associate in Philadelphia, PA is $18.91, according to ZipRecruiter salary data. Most workers in this role earn between $15.53 and $20.14 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 Philadelphia, PA are hiring for Machine Learning Data Associate jobs?

Cities near Philadelphia, PA 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 Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $39,328 per year, or $18.9 per hour.

Principal Data Platform & Machine Learning Engineer

Malvern, PA

BE Group
See more jobs at BE Groupexternal

$132K - $177K/yr

Full-time

Re-posted 16 days ago

Job description

We are assisting our client in hiring for a Principal Data Platform & Machine Learning Engineer.

Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.

This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days each week.

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role will define the technical foundation that powers the company's next generation of predictive analytics and AI capabilities.

This is a highly hands-on Principal Engineering opportunity for someone who enjoys building platforms as much as building software. You'll establish the architecture, data pipelines, APIs, engineering standards, and machine learning infrastructure that enable intelligent products to scale across the business.

You'll work closely with Product, Engineering, and executive leadership while mentoring other engineers and helping shape the technical direction of the platform. This is an opportunity to influence architecture, modernize engineering practices, and build production AI capabilities that directly impact customers and the future of the business.

What We're Looking For
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
  • 7+ years of experience building large-scale data platforms, cloud-native applications, or production machine learning systems.
  • Strong Python and SQL development skills.
  • Experience designing scalable data architectures, APIs, distributed data processing solutions, and machine learning platforms.
  • Experience with Azure, Databricks, MLflow, CI/CD, infrastructure automation, and MLOps.
  • Proven ability to establish engineering standards, technical direction, and software best practices while remaining highly hands-on.
  • Experience mentoring engineers and collaborating across multiple technical disciplines.
Preferred Experience
  • Financial services, banking, lending, collections, credit risk, or fintech.
  • Designing enterprise-scale data platforms and machine learning infrastructure.
  • Building highly available, cloud-native SaaS applications.
  • AI-assisted software development tools and modern engineering practices.
  • Passion for solving complex technical challenges while helping other engineers succeed.