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Remote Bioinformatics Machine Learning Jobs (NOW HIRING)

Remote We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production ...

Machine Learning Engineer

Colorado Springs, CO · On-site +1

$100K - $160K/yr

Work in Linux-based, containerized development environments using VS Code Dev Containers, Remote ... in machine learning, data science, or backend software development. * Hands-on experience ...

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Machine Learning Engineer III

Austin, TX · On-site +1

$122K - $158K/yr

You will follow a hybrid work model with a mix of remote work and in-office collaboration. This role focuses on building and operating production-grade data and machine learning infrastructure that ...

New

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

We have hybrid offices in London, New York, and Singapore; this role is remote based in the San Francisco area. This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Employee divides their time between in-office and remote work. Access to an office location is ...

Senior Machine Learning Engineer

Cambridge, MA · On-site +1

$82K - $220K/yr

Summary: The Machine Learning Engineer (SMTS) designs and implements machine learning (ML ... bioinformatics, and more. Duties/Responsibilities * Designs and develops AI models to meet project ...

Senior Machine Learning Engineer

Cambridge, MA · On-site +1

$82K - $220K/yr

Summary: The Machine Learning Engineer (SMTS) designs and implements machine learning (ML ... bioinformatics, and more. Duties/Responsibilities Designs and develops AI models to meet project ...

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

Location- Remote Overview: As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data ...

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Remote Bioinformatics Machine Learning information

See salary details

$59.5K

$94.5K

$149.5K

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

As of Jun 21, 2026, the average yearly pay for remote bioinformatics machine learning in the United States is $94,474.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,500.00 and $129,500.00 per year, depending on experience, location, and employer.

How do remote bioinformatics machine learning professionals typically collaborate with cross-functional teams?

Remote bioinformatics machine learning professionals often work closely with biologists, data scientists, and software engineers. Collaboration is typically facilitated through virtual meetings, shared code repositories, and project management tools. Regular communication is essential to align on data requirements, model development, and interpretation of results. While remote work offers flexibility, it requires strong organizational skills and proactive engagement to ensure seamless teamwork and project success.

What is a Remote Bioinformatics Machine Learning specialist?

A Remote Bioinformatics Machine Learning specialist is a professional who applies machine learning techniques to biological data, such as genomics or proteomics, while working from a remote location. They analyze complex biological datasets to uncover patterns, make predictions, and contribute to advancements in areas like drug discovery, disease research, and personalized medicine. These specialists typically have strong skills in programming, statistics, biology, and data analysis, and collaborate with researchers and healthcare professionals through digital communication tools.

What are the key skills and qualifications needed to thrive as a Remote Bioinformatics Machine Learning Specialist, and why are they important?

To excel as a Remote Bioinformatics Machine Learning Specialist, a strong background in computational biology, statistics, and machine learning—often supported by an advanced degree in bioinformatics, computer science, or a related field—is essential. Proficiency with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with bioinformatics tools and databases are typically required. Excellent problem-solving, self-motivation, and clear communication skills help professionals collaborate effectively and independently in remote environments. These abilities are vital for developing accurate models, interpreting complex biological data, and contributing meaningful insights to scientific research.

What is the difference between Remote Bioinformatics Machine Learning vs Remote Computational Biologist?

AspectRemote Bioinformatics Machine LearningRemote Computational Biologist
Required CredentialsMaster's or PhD in Bioinformatics, Computer Science, or related fields; experience in machine learningMaster's or PhD in Biology, Bioinformatics, or related fields; strong computational skills
Work EnvironmentRemote, collaborative teams in biotech, pharma, or research institutionsRemote or on-site, working in research labs or academic settings
Industry UsageUsed in biotech, healthcare, and pharmaceutical industries for data analysis and model developmentCommon in academic research, biotech, and healthcare for biological data interpretation

Remote Bioinformatics Machine Learning focuses on developing algorithms and models to analyze biological data using machine learning techniques. In contrast, Remote Computational Biologist applies computational methods to biological research questions, often integrating diverse data types. Both roles require strong computational skills and often overlap, but the former emphasizes machine learning expertise, while the latter has a broader biological research scope.

More about Remote Bioinformatics Machine Learning jobs
What cities are hiring for Remote Bioinformatics Machine Learning jobs? Cities with the most Remote Bioinformatics Machine Learning job openings:
What are the most commonly searched types of Bioinformatics Machine Learning jobs? The most popular types of Bioinformatics Machine Learning jobs are:
What states have the most Remote Bioinformatics Machine Learning jobs? States with the most job openings for Remote Bioinformatics Machine Learning jobs include:
Infographic showing various Remote Bioinformatics Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 2% As Needed, 90% Full Time, 5% Part Time, 1% Temporary, and 1% Nights. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution, with an average salary of $94,474 per year, or $45.4 per hour.
Machine Learning Engineer

Other

Posted 24 days ago


Job description

Applied Machine Learning Engineer | Music Software (Multiple Roles open)
Role: Applied Machine Learning Engineer (Mid - Senior Opportunity) Company: Splash
Employment Type: Contract (3 months +, potential for extension) Location: Remote
We are seeking an Applied Machine Learning Engineer with a strong focus on practical solutions and software development (ability to work on both open-ended research problems and production-ready API code). In this role, you'll leverage off-the-shelf tools and custom-built ML models to solve challenges in music product development and improve manual music processes. This position is ideal for engineers with demonstrable experience building functional, production-ready models and who are passionate about user experience and Product.
Key Responsibilities:
• Design and implement ML algorithms to enhance music creation tools and solve various user problems in line with product goals.
• Identify and implement off-the-shelf ML and AI tools to solve practical problems efficiently.
• Understand the requirements of running models in production, including domain shift testing, QA, A/B testing and so on.
• Maintain production-ready code with considerations for how solutions fit the product and enhance the user experience.
• Build scalable, maintainable data pipelines to handle audio and other unstructured data.
• Collaborate with Product and Engineering teams to ensure seamless integration of ML solutions into production systems.
• Evaluate, deploy, and fine-tune pre-trained models for tasks like audio analysis, melody generation, and process automation.
• Uphold ethical AI practices, ensuring fairness and responsible AI use in music-related applications.
What You Bring
• Proven software development experience, ideally in Python (other languages a plus).
• Experience implementing and deploying ML models, using PyTorch framework.
• Familiarity with AWS cloud environment for deploying and scaling ML solutions.
• Ability to preprocess and model unstructured data, especially audio.
• A strong focus on applied problem-solving, with a practical approach to integrating existing tools and systems.
• A good understanding of music, production, or audio technology processes (or a strong interest in music)
• Familiarity with GenAI architectures like transformers, LLMs, or diffusion models.
• Proactive nature, ability to creatively solve problems you face and bring new ideas to the team.
• Clear and effective communication with technical and non-technical stakeholders.
• Ability to work independently and remotely while collaborating closely with cross-functional teams.