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Remote Healthcare Machine Learning Jobs in Dallas, TX

YO AI Labs

Healthcare Attorney - Remote

Dallas, TX · Remote

$140 - $400/hr

Job Title: Healthcare Attorney Job Type: Contractor Location: Remote (United States Only) Job Overview We are seeking experienced Healthcare Attorneys to contribute their legal expertise to an ...

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.

Ironside Human Resources

Healthcare Recruiter

Dallas, TX · On-site +1

$40K - $60K/yr

Fully in office (remote/hybrid roles are not an option) * Base salary with uncapped commissions in ... Heavy phone dialing position with daily dials objective * Healthcare Recruiter must abide by all ...

Ironside Human Resources

Healthcare Recruiter

Dallas, TX · On-site +1

Fully in office (remote\/hybrid roles are not an option) \n * Base salary with uncapped commissions ... Heavy phone dialing position with daily dials objective \n * Healthcare Recruiter must abide by all ...

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

Remote Healthcare Machine Learning information

See Dallas, TX salary details

$25.2K

$42.1K

$87.1K

How much do remote healthcare machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for remote healthcare machine learning in Dallas, TX is $42,125.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,500.00 per year, depending on experience, location, and employer.

What is a remote healthcare machine learning professional?

A Remote Healthcare Machine Learning professional is someone who applies machine learning techniques and data analysis to healthcare-related problems while working remotely. They develop algorithms and models to analyze medical data, predict patient outcomes, and improve healthcare delivery. These professionals may work on projects like disease prediction, medical imaging analysis, or personalized treatment recommendations, often as part of a distributed team. Their work helps healthcare organizations leverage data to make informed decisions and improve patient care, all while working from a location outside of a traditional office or hospital setting.

How does a remote healthcare machine learning professional collaborate with clinical teams to implement AI solutions?

Remote Healthcare Machine Learning professionals often work closely with clinicians, data engineers, and IT staff to ensure that AI models address real clinical needs and comply with healthcare regulations. Collaboration usually involves regular virtual meetings, shared project management tools, and iterative feedback cycles where clinicians provide insights on data relevance and model outputs. Effective communication is crucial to bridge the gap between technical and medical expertise, ensuring solutions are both accurate and practical for everyday clinical use.

What are the key skills and qualifications needed to thrive as a remote healthcare machine learning specialist?

To thrive as a Remote Healthcare Machine Learning Specialist, you need a strong background in data science, statistics, machine learning algorithms, and healthcare domain knowledge, typically supported by a relevant degree in computer science, engineering, or biomedical informatics. Proficiency with programming languages (such as Python or R), machine learning frameworks (like TensorFlow or PyTorch), and experience with electronic health record (EHR) systems or health data standards is essential. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to non-technical stakeholders make someone stand out in this role. These skills are crucial for developing effective, compliant, and impactful healthcare solutions that improve patient outcomes and enable remote care delivery.

What is the difference between Remote Healthcare Machine Learning vs Remote Healthcare Data Analyst?

AspectRemote Healthcare Machine LearningRemote Healthcare Data Analyst
Required CredentialsDegree in Computer Science, Data Science, or related field; knowledge of ML algorithmsDegree in Statistics, Data Analysis, or related field; proficiency in data visualization
Work EnvironmentCollaborates with data scientists and engineers; focuses on developing modelsAnalyzes healthcare data; reports insights to stakeholders
Industry UsageDevelops predictive models for patient outcomes, diagnosticsInterprets healthcare data to inform decisions and improve processes

Remote Healthcare Machine Learning specialists focus on creating algorithms and models to predict health trends, while Remote Healthcare Data Analysts interpret healthcare data to support decision-making. Both roles require strong analytical skills but differ in technical focus and responsibilities.

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

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

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

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

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

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

Remote Healthcare Machine Learning jobs near you

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Dallas, TX • On-site, Remote

$157K - $234K/yr

Full-time

Re-posted 7 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor’s degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Experience managing technology such as JupyterHub and Kubeflow.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning – Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.