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Flexible Machine Learning Engineer Biotech Jobs (NOW HIRING)

Errgo

NY · On-site

$120 - $160/hr

Python PyTorch TensorFlow AWS MLOps Spark About the role As a Machine Learning Engineer, the ... Flexible PTO * Hybrid work options Job details and compensation are subject to change. #J-18808 ...

3B Staffing LLC

Machine Learning Engineer

Tahoma, CA · On-site

Machine Learning Engineer (Molecular Design) Location: Hybrid - Bay Area, CA We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery ...

New

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)

ExaCare Inc

Machine Learning Engineer

Manhattan, NY · On-site

$100 - $130/hr

Machine Learning Engineer ExaCare Inc - New York, New York, United States About this position ... Flexible PTO, take what you need * Medical, dental, and vision coverage * Great startup culture ...

Booz Allen Hamilton

Machine Learning Engineer

Aurora, CO · On-site

$78 - $176/hr

As a programmer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes using ML techniques ...

Qubeaxis

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Flexible working hours with a core collaboration window; 25 days annual leave. Job Overview Job ID 20985 Job Title Machine Learning Engineer Work Mode Onsite Experience 0-3 Years Ready to Apply?

3B Staffing LLC

Machine Learning Engineer

Tahoma, CA · On-site

Machine Learning Engineer (Molecular Design) Location: Hybrid - Bay Area, CA We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery ...

New

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

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)

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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 Sep 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.

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Flexible Machine Learning Engineer Biotech jobs near you
Infographic showing various Flexible Machine Learning Engineer Biotech job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 29% Part Time, and 3% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Errgo

NY • On-site

$120 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

Python PyTorch TensorFlow AWS MLOps Spark

About the role

As a Machine Learning Engineer, the candidate will design, build, and deploy ML models that solve complex business problems at scale. This role owns the full ML lifecycle—from problem formulation and data preparation through model training, evaluation, and production deployment—with a focus on building systems that are reliable, performant, and maintainable.The engineer will work at the intersection of research and engineering, translating state-of-the-art ML techniques into production systems that serve real users. They will collaborate with data engineers to build robust feature pipelines, partner with product teams to identify high-impact ML applications, and establish MLOps practices that enable rapid experimentation and deployment.The ideal candidate combines deep ML expertise with strong software engineering skills. They are comfortable working across the stack, from distributed training infrastructure to model serving and monitoring. This role offers significant ownership and the opportunity to shape ML strategy and architecture.

What you'll do
  • Design and implement machine learning models to solve business problems
  • Build end-to-end ML pipelines for training, evaluation, and deployment
  • Develop and maintain feature engineering pipelines
  • Optimize model performance for accuracy, latency, and cost
  • Deploy models to production using AWS SageMaker, Kubernetes, or similar
  • Implement monitoring and alerting for model performance in production
  • Collaborate with data engineers, product managers, and stakeholders
  • Stay current with ML research and evaluate new techniques for applicability
What you bring
  • 3-6 years of experience in machine learning engineering or applied ML
  • Strong Python skills with deep experience in PyTorch or TensorFlow
  • Experience training and deploying models in production environments
  • Solid understanding of ML fundamentals (deep learning, classical ML, optimization)
  • Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, or similar)
  • Familiarity with MLOps practices (experiment tracking, model versioning, CI/CD)
  • Experience with distributed computing (Spark, Ray) is a plus
  • Strong communication skills and ability to work cross-functionally
What you get
  • Medical, dental, and vision insurance
  • 401(k)
  • Equity
  • Flexible PTO
  • Hybrid work options

Job details and compensation are subject to change.

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