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Freelance Bioinformatics Machine Learning Jobs (NOW HIRING)

Education: * Master's or higher degree (PhD preferred) in Bioinformatics, Machine Learning and AI, Computer Science, Data Science or related quantitative field. * Experience: * 8+ years of ...

... machine learning algorithms for implementation within the ROSALIND multi-tenant SaaS platform • Be flexible and passionate about bioinformatics alchemy to support greater discovery into biology ...

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Freelance Bioinformatics Machine Learning information

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How much do freelance bioinformatics machine learning jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for freelance bioinformatics machine learning in the United States is $31.25, according to ZipRecruiter salary data. Most workers in this role earn between $12.02 and $50.48 per hour, depending on experience, location, and employer.

What does a Freelance Bioinformatics Machine Learning specialist do?

A Freelance Bioinformatics Machine Learning specialist applies machine learning techniques to analyze biological data, such as genomics, proteomics, and medical records, on a project-by-project basis. They typically work independently with research labs, biotech companies, or healthcare organizations to develop algorithms, build predictive models, and interpret complex biological datasets. Their work helps drive insights in areas like drug discovery, personalized medicine, and disease prediction, often leveraging tools like Python, R, and specialized bioinformatics software. As freelancers, they have the flexibility to choose projects, set their schedules, and work remotely.

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

To thrive as a Freelance Bioinformatics Machine Learning Specialist, you need a strong background in biology, statistics, and programming (such as Python or R), typically supported by a relevant degree in bioinformatics, computer science, or a related field. Familiarity with bioinformatics tools (e.g., BLAST, Bioconductor), machine learning libraries (scikit-learn, TensorFlow), and experience with cloud computing platforms are highly valuable. Strong problem-solving, communication, and project management skills help distinguish top freelancers in this field. These capabilities are crucial for independently delivering accurate, actionable biological insights to clients and efficiently managing multiple projects.

What are some common challenges freelance bioinformatics machine learning professionals face when working with multiple clients?

Freelance bioinformatics machine learning professionals often encounter challenges such as managing diverse data formats, aligning project expectations, and ensuring data privacy across multiple clients. Each client may have unique datasets, varying levels of documentation, and different computational infrastructure, requiring adaptability and strong communication skills. Balancing multiple deadlines and maintaining clear, consistent reporting are also important to foster trust and long-term collaborations.

What is the difference between Freelance Bioinformatics Machine Learning vs Freelance Data Scientist?

AspectFreelance Bioinformatics Machine LearningFreelance Data Scientist
CredentialsBackground in bioinformatics, biology, or related fields; knowledge of machine learningBackground in statistics, computer science, or related fields; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic projects, freelance consultingVarious industries including finance, tech, healthcare, consulting
Industry UsagePrimarily biotech, healthcare, genomics, pharmaceutical sectorsBroad industry application including finance, marketing, tech, healthcare

Freelance Bioinformatics Machine Learning specialists focus on applying machine learning techniques to biological data, often working within biotech and healthcare sectors. In contrast, Freelance Data Scientists have a broader scope, working across multiple industries with diverse datasets. Both roles require strong analytical skills and programming expertise, but their industry focus and domain knowledge differ significantly.

More about Freelance Bioinformatics Machine Learning jobs
What cities are hiring for Freelance Bioinformatics Machine Learning jobs? Cities with the most Freelance 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 Freelance Bioinformatics Machine Learning jobs? States with the most job openings for Freelance Bioinformatics Machine Learning jobs include:
Infographic showing various Freelance Bioinformatics Machine Learning job openings in the United States as of July 2026, with employment types broken down into 3% Locum Tenens, 50% Full Time, 8% Part Time, 1% Contract, 34% Nights, and 4% Summer. Highlights an 80% Physical, 3% Hybrid, and 17% Remote job distribution, with an average salary of $64,999 per year, or $31.2 per hour.

Sr. Bioinformatics ML/AI Engineer

Baylor Genetics

Houston, TX • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Baylor Genetics rating

8.4

Company rating: 8.4 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

25th of 120 rated laboratories


Job description

Job Summary:
Baylor Genetics is a company specializing in genetic testing and bioinformatics solutions. They are seeking a seasoned machine learning and AI application engineer to develop and support their next-generation bioinformatics ML/AI platform, focusing on genomic and clinical data modeling and application development.
Responsibilities:
• Serves as the SME in Bioinformatics ML/AI application development in a clinical genetic testing setting. Provides hands-on support towards building the company’s next-generation bioinformatics ML/AI platform
• Designs, develops, evaluates, and deploys state-of-the-art ML/AI solutions to gain valuable data insights based on the genetical, phenotypical, and clinical datasets
• Evaluates, adopts, and customizes GenAI models based on both internal and external datasets to enhance the overall performance of the genetic testing workflow
• Supports both internal and external data requirements by leveraging AI/ML and GenAI capabilities to keep up with the increasing demands of the business
• Collaborates in a multidisciplinary and regulated clinical diagnostics environment with geneticists, bioinformaticians, software engineers, and IT infrastructure professionals
Qualifications:
Required:
• Master's or higher degree in Computer Engineering, Data Science, Bioinformatics, Machine Learning, and Data modeling, or related field with five (5) years of experience in genomic data analysis and application development.
• Hands-on experience in clinical bioinformatics pipeline development, including secondary/tertiary analysis, variant interpretation and classification pipeline R&D, and automated report generation
• Hands-on experience in human genetics/multi-omics data modeling and application development, especially in next-generation sequencing data
• Hands-on experience in machine learning framework (such as Huggingface, TensorFlow)
• Hands-on experience in automated and scalable AI/GenAI application evaluation, development, and deployment.
• Hands-on experience in RAG AI framework
• Hands-on experience with scripting languages, such as Bash and Python
• Strong experience in cloud platform (Azure) and data services (data lakehouse/data warehouse)
• Experience in context-aware OCR
• Experience in databases, including SQL and NoSQL
• Familiarity with advanced data visualization techniques
• Strong curiosity and the ability to learn quickly and adapt to a fast-changing environment
Preferred:
• DevOps experience such as unit testing, CI/CD is a plus.
Company:
Baylor Genetics offers a full spectrum of cost-effective, genetic testing, and provides clinically relevant solutions. Founded in 1978, the company is headquartered in Houston, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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