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Remote Healthcare Machine Learning Jobs in Washington, DC

Staff Machine Learning Engineer Overview: As a Capital One Machine Learning Engineer, you'll be ... Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

We handle the logistics--you just invoice for your tutoring sessions, and we take care of payments. What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ...

Showing results 41-60

Remote Healthcare Machine Learning information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

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

As of Sep 12, 2026, the average yearly pay for remote healthcare machine learning in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 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.

Infographic showing various Remote Healthcare Machine Learning job openings in Washington, DC as of June 2026, with employment types broken down into 3% As Needed, 77% Full Time, 17% Part Time, and 3% Contract. Highlights an 51% Physical, 3% Hybrid, and 46% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.

Machine Learning Engineer with SageMaker Experience

Ashburn, VA • On-site, Remote

Maxiom Technology
IT Services • 11 - 50 employees

Full-time

Re-posted 12 days ago


Job description

Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? Do you thrive in a dynamic and innovative environment, eager to push the boundaries of AI capabilities? If so, we invite you to join our team as we revolutionize the world of AI-driven applications.

Position: Machine Learning Engineer
Location: Remote

Preferred Resource Location: LATAM

About Us:
Maxiom Technology is a cutting-edge technology company at the forefront of AI-driven solutions. We specialize in developing intelligent applications that leverage the power of machine learning and natural language processing. Our team consists of talented individuals who are dedicated to creating groundbreaking solutions that transform industries.

Responsibilities:

- Collaborate with cross-functional teams to design, develop, and deploy machine learning models using Amazon SageMaker.
- Utilize your expertise in prompt engineering to craft effective inputs for LLM models to achieve desired outputs.
- Fine-tune and optimize LLM models to enhance performance, efficiency, and accuracy.
- Design and implement experiments to evaluate model performance, iteratively improving results.
- Stay up-to-date with the latest advancements in machine learning, particularly in the realm of LLM models and prompt engineering techniques.
- Identify and troubleshoot issues related to model performance, data quality, and integration.
- Contribute to the entire machine learning lifecycle, from data preprocessing and training to deployment and monitoring.
- Collaborate with software engineers to integrate machine learning solutions into our applications.
- Document your work, best practices, and findings to share knowledge across the team.

Qualifications:

- Bachelor's degree in Computer Science, Engineering, or a related field (Master's or PhD preferred).
- Proven experience in developing and deploying machine learning models using Amazon SageMaker.
- Strong background in prompt engineering techniques for fine-tuning LLM models.
- Proficiency in programming languages such as Python for model development and experimentation.
- Solid understanding of natural language processing concepts and techniques.
- Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and their integration with SageMaker.
- Experience with data preprocessing, feature engineering, and data augmentation.
- Problem-solving skills to diagnose and address model performance and data-related issues.
- Excellent communication skills to collaborate effectively within multidisciplinary teams.
- Ability to adapt to evolving technologies and learn quickly in a fast-paced environment.

Bonus Skills:

- Publications or contributions to the machine learning community.
- Experience with cloud services (AWS, Azure, Google Cloud) and containerization technologies.
- Knowledge of DevOps practices for model deployment and monitoring.

Why Join Us:

- Opportunity to work on cutting-edge projects that push the boundaries of AI technology.
- Collaborative and inclusive work environment that values innovation and creativity.
- Access to resources and support for continuous learning and professional growth.
- Competitive compensation package and benefits.
 

If you are an ambitious Machine Learning Engineer with a proven track record in SageMaker, prompt engineering, and LLM model tuning, we would love to hear from you. Join us in our mission to create groundbreaking AI solutions that shape the future. Apply now by sending your resume and a cover letter.

Maxiom Technology is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.