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Healthcare Machine Learning Jobs in Dallas, TX (NOW HIRING)

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Hands-on experience with monitoring tools for ML pipeline health and performance. * Strong ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Hands-on experience with monitoring tools for ML pipeline health and performance. * Strong ...

System One

Machine Learning Operations Engineer

Dallas, TX · On-site

$68K - $93K/yr

Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC ... Hands-on experience with monitoring tools for ML pipeline health and performance. * Strong ...

Elevance Health

Research Scientist Senior

Grand Prairie, TX · On-site +1

$93K - $118K/yr

Develops scalable machine learning and reinforcement learning systems that improve healthcare outcomes, operational efficiency, and member experience through adaptive learning and advanced analytics.

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All JobsHealthcare Machine Learning JobsHealthcare Machine Learning Jobs in Dallas, TX

Healthcare Machine Learning information

See Dallas, TX salary details

$10.9K

$96.9K

$158.8K

How much do healthcare machine learning jobs pay per year?

As of Aug 22, 2026, the average yearly pay for healthcare machine learning in Dallas, TX is $96,944.00, according to ZipRecruiter salary data. Most workers in this role earn between $21,800.00 and $158,300.00 per year, depending on experience, location, and employer.

What is a healthcare machine learning?

A Healthcare Machine Learning job involves developing and applying machine learning models to analyze medical data and improve healthcare outcomes. Professionals in this role work with electronic health records, medical imaging, genomics, and other healthcare data to assist in disease prediction, diagnosis, and personalized treatments. They collaborate with clinicians, data scientists, and engineers to ensure models are clinically relevant and ethically sound. Strong knowledge of machine learning, data preprocessing, and regulatory compliance (such as HIPAA) is essential.

What are the key skills and qualifications needed to thrive in healthcare machine learning?

To thrive in Healthcare Machine Learning, you need strong expertise in data science, machine learning algorithms, and biomedical informatics, often supported by an advanced degree in computer science, statistics, or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and healthcare data standards (like HL7 or FHIR) is highly beneficial, and certifications in data science or health informatics can provide an edge. Excellent problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to diverse healthcare teams are valuable soft skills. These competencies are vital for developing robust, ethically sound machine learning solutions that improve clinical decision-making and patient outcomes.

What are some common challenges faced by professionals working in healthcare machine learning?

Professionals in Healthcare Machine Learning often encounter challenges such as navigating complex, unstructured, or incomplete healthcare data while ensuring strict compliance with privacy regulations like HIPAA. They must also bridge the gap between technical requirements and clinical needs, collaborating closely with medical professionals who may not have a technical background. Additionally, validating and interpreting machine learning models for real-world clinical use adds another layer of complexity, as solutions must be both accurate and explainable. Overcoming these challenges requires strong technical skills, effective teamwork, and a commitment to ethical, patient-centered solutions.

What does machine learning do in healthcare?

Healthcare machine learning involves developing algorithms that analyze medical data to assist in diagnosis, treatment planning, and predicting patient outcomes. Professionals in this field use tools like Python and TensorFlow, and often require knowledge of medical terminology and data privacy regulations to improve healthcare delivery.

What are the most commonly searched types of Healthcare Machine Learning jobs in Dallas, TX?

The most popular types of Healthcare Machine Learning jobs in Dallas, TX are:

What are popular job titles related to Healthcare Machine Learning jobs in Dallas, TX?

For Healthcare Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Healthcare Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Healthcare Machine Learning jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Healthcare Machine Learning jobs?

Cities near Dallas, TX with the most Healthcare Machine Learning job openings:

Healthcare Machine Learning jobs near you
Infographic showing various Healthcare Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $96,944 per year, or $46.6 per hour.

Machine Learning Operations Engineer

System One

Dallas, TX • On-site

$68K - $93K/yr

Contractor

Re-posted 13 days ago

Job description

Job Title: Machine Learning Operations Engineer Location: Dallas, Texas Type: Contract To Hire Visa : USC, GC, EAD (Only W2, No Sponsorship)

Responsibilities

  • Optimize and maintain large-scale feature engineering pipelines using PySpark, Pandas, and PyArrow on Hadoop-based infrastructure.
  • Refactor and modularize ML codebases to enhance reusability, maintainability, and performance.
  • Collaborate with platform teams on compute capacity planning, resource allocation, and system upgrades.
  • Integrate with existing model serving frameworks to support testing, deployment, and rollback processes.
  • Monitor and troubleshoot production ML pipelines, ensuring high reliability, low latency, and cost efficiency.
  • Contribute to internal ML platforms by sharing insights, proposing improvements, and documenting best practices.
  • Build near real-time ML pipelines using Kafka and Spark Streaming.
  • Work with AWS and SageMaker MLOps ecosystem.
Requirements
  • 6+ years of experience in software engineering, data engineering, or MLOps roles.
  • Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow.
  • Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
  • Experience with CI/CD pipelines and best practices in ML environments.
  • Hands-on experience with monitoring tools for ML pipeline health and performance.
  • Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering).
  • Experience contributing to or building internal MLOps frameworks/platforms.
  • Familiarity with SLURM clusters or other distributed job schedulers.
  • Exposure to Kafka, Spark Streaming, or other real-time data processing technologies.
  • Understanding of ML lifecycle management, including versioning, deployment, and drift detection.

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About System One

Sourced by ZipRecruiter

System One helps employers get work done more efficiently and economically without compromising quality. Over our 35+ year history, we've helped connect thousands of talented people with innovative companies. The excitement of a perfect fit motivates us every single day.

Industry

Business consulting services and recruiting and staffing services

Company size

5,001 - 10,000 Employees

Headquarters location

Pittsburgh, PA, US

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