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Machine Learning Engineer Biotech Jobs in Durham, NC

As a Machine Learning Engineer, you will help build and operate production systems that power fraud detection and risk-related products. You'll work closely with data scientists and engineers to ...

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the ...

Machine Learning Engineer Lenovo is building Quantum, a next-generation hybrid AI platform that spans Windows, Android, and cloud. As part of this initiative, we are growing the engineering ...

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115K - $192K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

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Machine Learning Engineer Biotech information

See Durham, NC salary details

$30.4K

$124.4K

$187K

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

As of Jun 10, 2026, the average yearly pay for machine learning engineer biotech in Durham, NC is $124,430.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,100.00 and $149,800.00 per year, depending on experience, location, and employer.

What does a Machine Learning Engineer do in the biotech industry?

A Machine Learning Engineer in biotech applies advanced algorithms and data analysis techniques to solve biological and medical problems. They work with large datasets such as genomic sequences, medical images, or clinical records to develop predictive models, automate data analysis, and uncover insights that can accelerate drug discovery, diagnostics, and personalized medicine. Their work often involves close collaboration with biologists, data scientists, and software engineers to create tools and solutions that improve healthcare outcomes. Machine Learning Engineers in this field need a strong background in both computational methods and biological sciences.

How do Machine Learning Engineers in biotech typically collaborate with research scientists and domain experts?

Machine Learning Engineers in biotech often work closely with research scientists and domain experts to translate complex biological problems into data-driven solutions. This collaboration involves regular meetings to understand experimental data, refine project goals, and iterate on model development based on domain feedback. Engineers are expected to communicate technical concepts clearly, adapt models to fit scientific needs, and help validate results alongside laboratory teams. This interdisciplinary environment fosters innovation but also requires flexibility and strong communication skills.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer in Biotech, and why are they important?

To thrive as a Machine Learning Engineer in Biotech, you need a solid background in computer science, statistics, and biology, often with an advanced degree in a related field. Experience with programming languages such as Python or R, machine learning frameworks like TensorFlow or PyTorch, and familiarity with bioinformatics tools are typically required. Strong problem-solving, communication, and interdisciplinary collaboration skills set standout candidates apart. These capabilities are crucial for developing effective models that drive scientific innovation and advance biotechnological research.

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

AspectMachine Learning Engineer BiotechData Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related; knowledge of ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, coding, deploying algorithms in biotech R&DAnalyzes biological data, interprets results, creates reports
Employer & Industry UsageBiotech firms, pharma companies, research labsBiotech companies, healthcare, research institutions

While both roles work with biological data, Machine Learning Engineers focus on developing and deploying ML algorithms, whereas Data Scientists analyze and interpret biological datasets to inform research and decision-making in biotech settings.

What are popular job titles related to Machine Learning Engineer Biotech jobs in Durham, NC? For Machine Learning Engineer Biotech jobs in Durham, NC, the most frequently searched job titles are:
What cities near Durham, NC are hiring for Machine Learning Engineer Biotech jobs? Cities near Durham, NC with the most Machine Learning Engineer Biotech job openings:

Other

Posted 21 days ago


Job description

The Risk & Fraud team helps customers take a proactive stance against fraud while managing the risks inherent to their business. We build and enhance products that evolve with the ever-changing fraud landscape, delivering tangible value to customers. Our solutions allow financial institutions to focus more of their time and energy on serving their customers and communities.

As a Machine Learning Engineer, you will help build and operate production systems that power fraud detection and risk-related products. You’ll work closely with data scientists and engineers to bring models into production, ensuring they are reliable, scalable, and maintainable.

You’ll gain hands-on experience working across model development, evaluation, deployment, monitoring, and ongoing improvements. This is an applied engineering role — the software you build will solve real-world problems and must be production-ready, reliable, and testable.

A Typical Day

Your Key Responsibilities

  • Build and maintain systems and pipelines that support training, evaluation, and inference for machine learning models

  • Contribute to deploying machine learning models into production environments and ensuring they run reliably at scale

  • Write clean, maintainable, and well-tested code following production engineering best practices

  • Support monitoring and troubleshooting production ML systems, including data pipelines and model performance

  • Collaborate with data scientists and engineers to productionalize models and integrate them into scalable applications

  • Help improve the reliability, scalability, and performance of ML systems over time

  • Contribute to improving tooling and infrastructure that supports the ML development lifecycle

You Are More Likely to Excel If You:

  • Enjoy autonomy in your work and take ownership of team goals while balancing speed with long-term impact

  • Have empathy for end users and measure success through both customer value and technical quality

  • Are enthusiastic about machine learning, engineering excellence, and continuous professional development

Bring Your Passion, Do What You Love. Here’s What We’re Looking For

Must-Haves

  • Bachelor’s degree in a relevant field with 2+ years of related experience, or equivalent practical experience

  • Proficiency in Python

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

Nice to Have

  • Experience building end-to-end ML systems, including data pipelines, model training, deployment, and monitoring

  • Experience deploying or integrating machine learning models into applications

  • Experience building APIs, backend services, or working with distributed systems

  • Familiarity with cloud platforms such as AWS, GCP, or Azure

  • Exposure to MLOps concepts such as CI/CD and model monitoring

  • Experience working with large datasets or data processing frameworks

  • Experience with additional programming languages such as TypeScript