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Flexible Junior Machine Learning Engineer Jobs (NOW HIRING)

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ... Competitive compensation, benefits, flexible time off, and career development opportunities

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Flexible work schedule * Tuition support * PTO and paid holidays Visit us: www.covar.com

Machine Learning Engineer LOCATIONReston, VA 20190 CLEARANCETS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

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How much do flexible junior machine learning engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for flexible junior machine learning engineer in the United States is $71,799.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,000.00 per year, depending on experience, location, and employer.
What are the most commonly searched types of Junior Machine Learning Engineer jobs? The most popular types of Junior Machine Learning Engineer jobs are:
Machine Learning Engineer

Machine Learning Engineer

Upperline Health

Nashville, TN • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Upperline Health rating

3.0

Company rating: 3.0 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Position Overview: We are looking for a talented Machine Learning Engineer to help build and maintain machine learning pipelines that support predictive healthcare models. This role is ideal for someone with strong data engineering skills and a passion for applying machine learning to real-world healthcare challenges.
Key Responsibilities:
  • Design and implement data pipelines using SQL and Python from various data sources.
  • Synthesize large medical claims data records into useable data features.
  • Collaborate with Data Scientists to build, refine, and deploy various machine learning models in Python.
  • Learn and apply SAS as needed for dataset generation (prior experience is not required).
  • Ensure data quality, reproducibility, and performance in the pipelines.
  • Contribute to best practices for data governance and model deployment.

Qualifications:
  • 2-5+ YOE as a Machine Learning Engineer or Data Scientist with a focus on engineering data builds.
  • Proficiency in SQL/Snowflake and Python; willingness to learn SAS as needed.
  • Experience building and combining data pipelines and working with large datasets.
  • Basic understanding of healthcare claims data (e.g., Medicare claims) preferred.
  • Familiarity with machine learning workflows (e.g., scikit-learn, pandas, NumPy).
  • Strong problem-solving and communication skills, sharp critical thinking skills.
  • Comfortable with a fast-paced workstream that requires flexibility to work on multiple projects or analyses at the same time.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

What Upperline Health employees say

Hours and flexibility

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