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Flexible Machine Learning Engineer Biotech Jobs (NOW HIRING)

Spotify

Machine Learning Engineer

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Honolulu, HI · On-site

Machine Learning Engineer LOCATION Honolulu, HI 96815 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Flexible Work Schedule * Cafeteria Style Benefits * 10% - 401k Matching (Vested Immediately)

ExtendMyTeam

Machine Learning Engineer

Austin, TX

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ... Competitive compensation, benefits, flexible time off, and career development opportunities

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

CoVar

Machine Learning Engineer

Durham, NC

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC ... Flexible work schedule * Tuition support * PTO and paid holidays Visit us: www.covar.com

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All JobsFlexible Machine Learning Engineer Biotech Jobs

Flexible Machine Learning Engineer Biotech information

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$31.5K

$128.8K

$193.5K

How much do flexible machine learning engineer biotech jobs pay per year?

As of Jul 4, 2026, the average yearly pay for flexible machine learning engineer biotech in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Flexible Machine Learning Engineer Biotech vs Data Scientist Biotech?

AspectFlexible Machine Learning Engineer BiotechData Scientist Biotech
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML frameworksDegree in Statistics, Mathematics, or related fields; proficiency in data analysis
Work EnvironmentDevelops and deploys ML models in biotech R&D and production settingsAnalyzes biological data to extract insights, often in research labs or biotech companies
Employer & Industry UsageUsed by biotech firms focusing on AI-driven drug discovery and diagnosticsCommon in biotech research, clinical data analysis, and bioinformatics

The main difference is that a Flexible Machine Learning Engineer Biotech primarily develops and implements machine learning models tailored for biotech applications, while a Data Scientist Biotech focuses on analyzing biological data to generate insights. Both roles require strong technical skills, but the engineer emphasizes model deployment and integration, whereas the scientist emphasizes data interpretation and statistical analysis.

More about Flexible Machine Learning Engineer Biotech jobs
What cities are hiring for Flexible Machine Learning Engineer Biotech jobs? Cities with the most Flexible Machine Learning Engineer Biotech job openings:
What are the most commonly searched types of Machine Learning Engineer Biotech jobs? The most popular types of Machine Learning Engineer Biotech jobs are:
What states have the most Flexible Machine Learning Engineer Biotech jobs? States with the most job openings for Flexible Machine Learning Engineer Biotech jobs include:
What job categories do people searching Flexible Machine Learning Engineer Biotech jobs look for? The top searched job categories for Flexible Machine Learning Engineer Biotech jobs are:
Flexible Machine Learning Engineer Biotech jobs near you
Infographic showing various Flexible Machine Learning Engineer Biotech job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 85% Full Time, and 14% Part Time. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Other

Posted 4 days ago

Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
Integrate machine learning systems into existing software architectures and enterprise platforms
Design, build, and optimize data pipelines to support model training and inference
Develop, test, and deploy machine learning models into production environments
Manage transition from prototype to production, including deployment pipelines and monitoring solutions
Monitor model performance, including handling model drift, rollback, and failure scenarios
Conduct experiments and testing to evaluate and improve model accuracy and performance
Write clean, maintainable, and testable code in Python and related technologies
Collaborate with cross-functional teams to integrate ML capabilities into mission systems
Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
Support development in Linux and Windows environments
Required:
Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
Strong programming skills in Python
Experience with machine learning frameworks, libraries, and data modeling techniques
Solid understanding of the machine learning lifecycle
Experience working with SQL and NoSQL databases
Experience working in Linux and Windows environments
Familiarity with CI/CD pipelines and Agile development methodologies
Understanding of software design and system integration principles
Desired:
Active TS/SCI with CI Polygraph (desired)
Experience working with large-scale (petabyte-level) datasets
Experience supporting multi-INT analytics environments
Experience deploying, monitoring, and scaling machine learning models in production
Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
Experience implementing GitOps workflows
Experience working in secure or classified environment

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