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Machine Learning Data Associate Jobs in Philadelphia, PA

Varsity Tutors

Data Science Tutor

Trenton, NJ · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Varsity Tutors

Data Science Tutor

Chester, PA · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Vangard, Inc.

Data Engineer, Specialist

Wayne, PA

$103K - $124K/yr

Machine Learning * Data Governance * Minimum of five years data analytics, programming, database administration, or data management experience. * Undergraduate degree or equivalent combination of ...

Vanguard Group, Inc.

Data Engineer, Specialist

Wayne, PA · On-site

$103K - $124K/yr

Machine Learning * Data Governance * Minimum of five years data analytics, programming, database administration, or data management experience. * Undergraduate degree or equivalent combination of ...

THE TILTED CIRCLE LLC

Data Science

West Point, PA · On-site

Strong core data science and machine learning experience, * Solid Python + scikit-learn + deep learning framework skills, * Experience with scikit-learn and at least one deep learning framework such ...

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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 Jun 28, 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 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.
Machine Learning Data Associate jobs near you
Infographic showing various Machine Learning Data Associate job openings in Philadelphia, PA as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $39,328 per year, or $18.9 per hour.
Senior Machine Learning Software Engineer

Senior Machine Learning Software Engineer

Penn Medicine

Philadelphia, PA • On-site

$123K - $163K/yr

Other

Posted 26 days ago

Penn Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 343 frontline employees who took The Breakroom Quiz

188th of 877 rated healthcare providers

Job description

Description
Penn Medicine is dedicated to our tripartite mission of providing the highest level of care to patients, conducting innovative research, and educating future leaders in the field of medicine. Working for this leading academic medical center means collaboration with top clinical, technical and business professionals across all disciplines.
Today at Penn Medicine, someone will make a breakthrough. Someone will heal a heart, deliver hopeful news, and give comfort and reassurance. Our employees shape our future each day. Are you living your life's work?
Entity: Corporate Services
Department: PennDNA Data Science
Location: 3600 Civic Center Blvd, Philadelphia, PA
Hours: M-F, Daylight
Summary:
Working with a team of data scientists and ML engineers, the Senior Machine Learning Software Engineer is responsible for the development, implementation, and maintenance of cutting-edge software for machine learning models and algorithms. The goal is to drive impactful insights and solutions across various healthcare domains, such as enhancing patient care, operational efficiency, and research endeavors. The ideal candidate will be a seasoned software engineer with experience in machine learning infrastructure and healthcare data. The Senior ML Software Engineer is both a member of a team, has expertise in one or more sub-domains, triages and refines requests, leads moderately complex projects and mentors more junior members of the team.
Responsibilities:
  • Systems and Software Engineering: Leverage proprietary and open-source tools and frameworks to develop ML systems and software applications. Design and implement scalable and modular software architectures, emphasizing maintainability and extensibility. Develop core capabilities for ML training, development, deployment and monitoring. Develop integrations with health system applications (e.g. Epic), systems and both on-prem and cloud infrastructure. Responsible for continuous integration and continuous delivery of production code. Independently lead and execute moderately complex projects with minimal oversight.
  • Model Deployment and Monitoring: Develop and enforce the technical standards for deployment of machine learning models for healthcare applications. Contribute to the deployment and monitoring of ML capabilities based on emerging technologies, trends and methodologies. Lead the design and development of tools for active monitoring of models and ML applications. Help maintain and optimize production models and applications.
  • Data Sourcing and Integration: Work with ML and data engineers to build robust and maintainable data pipelines for model development, validation, and deployment. Ensure seamless data integration and flow with health system applications that supports the scalability and efficiency of ML models and analytics platforms.
  • Collaboration: Collaborate with a multidisciplinary team, including data scientists, data and ML engineers, clinicians, administrators, and product managers to define project requirements and develop solutions that meet
  • organizational needs. This collaboration aims not only to advance healthcare technology but also to drive significant improvements in patient outcomes and operational efficiencies, demonstrating the tangible impact of our work. Provide subject matter expert review, guidance and consultation.
  • Continuous Improvement: Demonstrate a commitment to continuous learning and professional development. Stay current with emerging industry trends, best practices, and technologies in ML software engineering. Model a culture of performance excellence both within team and across the enterprise. Look for opportunities to optimize the team's processes and workflows.

Education or Equivalent Experience:
  • Bachelor's degree is required. Computer science or a related field with a focus on machine learning or data science.
  • 3+ years of experience and expertise in software engineering and infrastructure to support development and deployment of machine learning models and applications is required.
  • Proven track record of leading and executing moderately complex projects with minimal oversight is required.
  • 1+ years healthcare analytics experience is preferred.

We believe that the best care for our patients starts with the best care for our employees. Our employee benefits programs help our employees get healthy and stay healthy. We offer a comprehensive compensation and benefits program that includes one of the finest prepaid tuition assistance programs in the region. Penn Medicine employees are actively engaged and committed to our mission. Together we will continue to make medical advances that help people live longer, healthier lives.
Live Your Life's Work
We are an Equal Opportunity employer. Candidates are considered for employment without regard to race, ethnicity, color, sex, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, familial status, genetic information, domestic or sexual violence victim status, citizenship status, military status, status as a protected veteran or any other status protected by applicable law.

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