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Machine Learning Engineer Biotech Jobs in Dallas, TX

Optimum

Sr Machine Learning Engineer

Plano, TX · On-site

$97K - $134K/yr

Job Summary Machine Learning Engineers work to deploy end-to-end solutions to business problems leveraging AI and/or ML principles as needed to create those solutions. MLEs will take requests from ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners ...

Nexxen

Senior Machine Learning Engineer, AdTech

Dallas, TX · On-site +1

$180K - $220K/yr

Sr. Machine Learning Engineer Flexible advertising, unified by data. Nexxen empowers advertisers, agencies, publishers, and broadcasters around the world to utilize data and advanced TV in the ways ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Veho

Senior Machine Learning Platform Engineer

Dallas, TX · On-site

$103K - $142K/yr

The Senior Machine Learning Platform Engineer will work alongside data scientists and software engineers to create and maintain ML infrastructure, ensuring the deployment and performance of models in ...

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All JobsMachine Learning Engineer Biotech JobsMachine Learning Engineer Biotech Jobs in Dallas, TX

Machine Learning Engineer Biotech information

See Dallas, TX salary details

$31.2K

$127.4K

$191.4K

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

As of Jun 13, 2026, the average yearly pay for machine learning engineer biotech in Dallas, TX is $127,383.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,400.00 and $153,300.00 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 the most commonly searched types of Machine Learning Engineer Biotech jobs in Dallas, TX? The most popular types of Machine Learning Engineer Biotech jobs in Dallas, TX are:
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Machine Learning Engineer Biotech jobs near you

AI / Machine Learning Engineer (Python)

Prophecy Technologies

Plano, TX • On-site

Full-time

Posted 15 days ago

Job description

Job Summary
We are looking for a Senior AI / Machine Learning Engineer with strong expertise in Python and end-to-end AI solution development. The role involves designing, building, deploying, and optimizing machine learning and deep learning models while contributing to scalable, secure, and high-performance application architectures.
Key Responsibilities
  • Develop, train, optimize, and evaluate machine learning and deep learning models for business use cases
  • Build and deploy end-to-end AI solutions including data ingestion, model development, testing, and production integration
  • Design, develop, and maintain high-performance Python applications and services
  • Ensure scalability, reliability, and security of AI applications
  • Build and integrate RESTful APIs and third-party services
  • Automate workflows, data processing, and reporting using Python
  • Troubleshoot complex application and database issues and implement long-term solutions
  • Contribute to system architecture decisions and technology roadmaps
  • Lead code reviews, enforce best practices, and mentor junior engineers
  • Collaborate with product owners, data analysts, and stakeholders to translate business requirements into technical solutions

Required Skills & Experience
  • Strong hands-on experience with Python for application and AI development
  • Experience developing and deploying machine learning and deep learning models
  • Knowledge of end-to-end AI/ML pipelines including data ingestion, training, evaluation, and deployment
  • Strong understanding of RESTful API design and integration
  • Experience with scalable application architectures and cloud-native services
  • Strong debugging and troubleshooting skills across application and database layers

Competencies
  • Strong analytical and problem-solving skills
  • Ability to translate business problems into technical solutions
  • Leadership and mentoring capabilities
  • Excellent communication and collaboration skills
  • Ownership mindset and attention to code quality and performance

Preferred Skills
  • Experience with cloud platforms and MLOps practices
  • Exposure to system design and architecture planning
  • Familiarity with automation frameworks and CI/CD pipelines
  • Experience working in Agile development environments

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