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Remote Biomedical Machine Learning Jobs (NOW HIRING)

OmegaHires

AI / Machine Learning Roles (Remote, USA)

$87 - $117/hr

AI / Machine Learning Roles (Remote, USA) Location: Remote, USA Employment type: Contract Indicative rate: $87-$117/hr We are seeking talented professionals in the AI and Machine Learning domain to ...

New

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Canals

Machine Learning Engineer

Denver, CO · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

SmarterDx

Staff Software Engineer, Machine Learning

$250K/yr

This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven features across multiple products * Design reusable architecture that powers and accelerates machine ...

Paylocity

Staff Machine Learning Engineer

This is a fully remote position, allowing you to work from home or location of record within the U ... Our machine learning engineering team is responsible for developing infrastructure and tooling to ...

Paylocity

Senior Machine Learning Engineer

$125K - $165K/yr

This is a fully remote position, allowing you to work from home or location of record within the U ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Tomorrow.io

Machine Learning Scientist

Golden, CO · Remote

Knowledge of satellite remote sensing and experience working with satellite observations. * Experience developing production-quality scientific or machine learning software. * Familiarity with modern ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Remote Biomedical Machine Learning information

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$15

$28

$38

How much do remote biomedical machine learning jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for remote biomedical machine learning in the United States is $28.53, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $32.21 per hour, depending on experience, location, and employer.

What is a remote biomedical machine learning job?

Remote biomedical machine learning jobs involve applying machine learning and artificial intelligence techniques to biomedical data, such as medical images, genetic information, or clinical records, while working from a remote location. Professionals in these roles develop algorithms to assist in disease diagnosis, drug discovery, or patient outcome prediction. These jobs typically require strong programming skills, experience with data science tools, and a background in biomedical sciences or related fields. Remote positions offer flexibility and the ability to collaborate with interdisciplinary teams from anywhere in the world.

What are some unique challenges faced when working remotely as a biomedical machine learning professional, and how can they be addressed?

Remote Biomedical Machine Learning professionals often face challenges related to accessing large and sensitive datasets, ensuring compliance with data privacy regulations, and maintaining effective communication with interdisciplinary teams such as clinicians and researchers. To address these, it's important to become familiar with secure data transfer protocols, collaborate closely with IT and compliance officers, and utilize robust project management and communication tools. Regular virtual meetings and clear documentation can help bridge gaps and ensure alignment on project goals.

What are the key skills and qualifications needed to thrive as a remote biomedical machine learning specialist, and why are they important?

Thriving in Remote Biomedical Machine Learning requires expertise in machine learning, data analysis, and a strong background in biomedical sciences, often supported by an advanced degree in a related field. Proficiency with programming languages such as Python or R, experience with frameworks like TensorFlow or PyTorch, and familiarity with medical data systems are typically necessary. Excellent problem-solving skills, communication abilities, and self-motivation are standout soft skills for remote collaboration and research. These competencies are vital to effectively develop innovative biomedical solutions, ensure data integrity, and drive impactful research in a distributed work environment.

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

AspectRemote Biomedical Machine LearningRemote Biomedical Data Analyst
Required CredentialsMaster's or PhD in Bioinformatics, Data Science, or related fields; experience with ML frameworksBachelor's or Master's in Biology, Data Analysis, or related; proficiency in data visualization and statistical tools
Work EnvironmentCollaborative remote teams, research labs, tech companiesRemote healthcare organizations, research institutions, biotech firms
Employer & Industry UsageTech companies, biotech startups, research institutionsHospitals, healthcare providers, pharmaceutical companies

Remote Biomedical Machine Learning specialists focus on developing algorithms and models to analyze biomedical data, often requiring advanced degrees and programming skills. In contrast, Remote Biomedical Data Analysts interpret and visualize biomedical datasets, typically with a focus on statistical analysis. Both roles are vital in healthcare and biotech industries but differ in technical depth and responsibilities.

More about Remote Biomedical Machine Learning jobs

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The most popular types of Biomedical Machine Learning jobs are:

What states have the most Remote Biomedical Machine Learning jobs?

States with the most job openings for Remote Biomedical Machine Learning jobs include:

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What other helpful pages are available for Remote Biomedical Machine Learning?

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Remote Biomedical Machine Learning jobs near you
Infographic showing various Remote Biomedical Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $59,333 per year, or $28.5 per hour.

Machine Learning Engineer - Model Evaluation & Experimentation

Remote

Weekday AI
See more jobs at Weekday AIexternal

$60 - $90/hr

Part-time

Re-posted 12 days ago

Job description

This role is for one of our clients
Compensation: $60-$90 per hour
Join a pioneering AI initiative focused on building the next generation of evaluation benchmarks for frontier AI models. We are seeking experienced Machine Learning Engineers and Researchers to bring hands-on expertise in model development, experimentation, and evaluation to create rigorous benchmark tasks for advanced AI systems.
In this role, you will design sophisticated, multi-step machine learning challenges inspired by real-world research workflows. From implementing experimental ideas and running training pipelines to analyzing model behavior and validating results, you will help establish high-quality evaluation benchmarks that reveal the strengths and limitations of frontier AI models.
This is a fully remote, full-time engagement requiring approximately 35 hours per week.
Requirements
Key Responsibilities
  • Design realistic machine learning benchmark tasks based on research workflows, including model implementation, experimentation, training, evaluation, and performance analysis.
  • Translate open-ended research concepts into structured, reproducible evaluation tasks with clearly defined success criteria.
  • Implement machine learning solutions using Python, execute experiments, and produce reference implementations that demonstrate correct methodology and expected outcomes.
  • Develop benchmark tasks involving reinforcement learning concepts such as reward functions, policy optimization, training dynamics, and model behavior where applicable.
  • Evaluate AI-generated solutions by identifying implementation errors, experimental flaws, incorrect reasoning, and unsupported conclusions.
  • Collaborate with AI researchers and fellow subject matter experts to continuously improve benchmark quality, technical rigor, and evaluation consistency.
Required Qualifications
  • Master's degree, PhD, or equivalent practical experience in Machine Learning, Computer Science, Artificial Intelligence, Data Science, or another quantitative STEM discipline.
  • Minimum 1 year of professional experience in machine learning research, research engineering, applied AI, or another research-intensive technical role.
  • Strong hands-on experience designing, training, evaluating, and optimizing machine learning models through complete experimental workflows.
  • Practical experience conducting machine learning experiments, including experiment setup, hyperparameter tuning, execution, validation, and analysis.
  • Strong understanding of modern Large Language Models (LLMs), their capabilities, limitations, and evaluation methodologies.
  • Proficiency in Python and Git, with experience working in both script-based and notebook-based development environments.
  • Familiarity with reinforcement learning concepts-including reward functions, policy optimization, and training behavior-is preferred.
  • Experience with AI evaluation, benchmark development, AI training, or task authoring is highly desirable.
  • Excellent analytical thinking, creativity, attention to detail, and the ability to solve complex, open-ended technical problems independently.
  • Strong written communication skills for documenting experimental methodologies and technical findings.
  • Ability to commit approximately 35 hours per week on a consistent basis.
Preferred Qualifications
  • Experience developing or evaluating large language models, foundation models, or generative AI systems.
  • Background in reinforcement learning, deep learning, distributed training, or model optimization.
  • Familiarity with benchmark design, AI safety evaluations, or research-quality experimentation.
  • Experience contributing to research publications, open-source machine learning projects, or advanced AI systems.
Why Join
  • Help shape how next-generation AI systems are evaluated through rigorous machine learning experimentation.
  • Collaborate with leading AI researchers developing frontier evaluation benchmarks.
  • Apply your expertise to improve AI reasoning, model quality, and experimental reliability.
  • Contribute directly to benchmark development that advances the capabilities of state-of-the-art AI systems.
  • Enjoy the flexibility of a fully remote engagement while working on impactful AI research initiatives.
Equal Opportunity
We are committed to fostering an inclusive and diverse environment where all qualified applicants receive equal consideration. Reasonable accommodations are available throughout the application and engagement process.
Contract & Engagement Details
  • Independent contractor engagement.
  • Fully remote with flexible working hours.
  • Expected commitment of approximately 35 hours per week.
  • Project duration may be extended, shortened, or concluded based on project requirements and individual performance.
  • Work does not require access to confidential or proprietary information from any current or former employer.
  • Payments are issued weekly based on approved work completed.
  • At this time, we are unable to support H1-B or STEM OPT candidates.

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