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Machine Learning Engineer Biotech Jobs in Austin, TX

Q2

Machine Learning Engineer

Austin, TX · Hybrid

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

webAI

Staff Machine Learning Engineer

Austin, TX · On-site

They are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models and Mixture of Experts to lead the development and optimization of advanced AI models ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

Summary The Machine Learning Engineer designs and evolves enterprise AI systems and architectures that enable scalable, secure, and high-impact adoption across the organization. This role defines end ...

9 Mothers

Machine Learning Engineer, Senior

Austin, TX · On-site

$103K - $142K/yr

The company is seeking a Senior Machine Learning Engineer to design, train, and maintain models for their counter-sUAS perception stack, focusing on model research and dataset engineering.

Bespoke Labs

Machine Learning Engineer

Austin, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

San Marcos, TX · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Austin, TX

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Striveworks

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121K - $160K/yr

The Role As a Senior Machine Learning Engineer at Striveworks, you'll be challenged-and trusted-on day one to be a core contributor to both the customer-driven projects and the enduring products of ...

Iterable

Senior Machine Learning Engineer (Nova)

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer to build core Machine Learning foundations, focusing on applied Machine Learning in production environments, and collaborating with various teams ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Apple

Senior Machine Learning Engineer

Austin, TX

$184K - $318K/yr

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

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Showing results 1-20

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

Machine Learning Engineer Biotech information

See Austin, TX salary details

$31.2K

$127.6K

$191.8K

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

As of Jul 3, 2026, the average yearly pay for machine learning engineer biotech in Austin, TX is $127,637.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $153,600.00 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 Austin, TX? The most popular types of Machine Learning Engineer Biotech jobs in Austin, TX are:
What are popular job titles related to Machine Learning Engineer Biotech jobs in Austin, TX? For Machine Learning Engineer Biotech jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Biotech jobs in Austin, TX look for? The top searched job categories for Machine Learning Engineer Biotech jobs in Austin, TX are:
What cities near Austin, TX are hiring for Machine Learning Engineer Biotech jobs? Cities near Austin, TX with the most Machine Learning Engineer Biotech job openings:
Machine Learning Engineer Biotech jobs near you
Infographic showing various Machine Learning Engineer Biotech job openings in Austin, TX as of June 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $127,637 per year, or $61.4 per hour.

Staff Machine Learning Engineer

TalentPros.AI

Austin, TX

$120K - $550K/yr

Full-time

Posted 10 days ago

Job description

About the Team

We are at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll transform groundbreaking research into real-world applications that can change industries, enhance human creativity, and solve complex problems.


About the Role

As a Machine Learning Engineer in our Applied Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.

In this role, you will:

  • Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring our research from concept to implementation, creating AI-driven applications with a direct impact.
  • Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.
  • Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.
  • Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.
  • Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.


You might thrive in this role if you:

  • Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. 
  • Demonstrated experience in deep learning and transformers models
  • Proficiency in frameworks like PyTorch or Tensorflow
  • Strong foundation in data structures, algorithms, and software engineering principles.
  • Experience with search relevance, ads ranking or LLMs is a plus.
  • Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
  • Excellent problem-solving and analytical skills, with a proactive approach to challenges.
  • Ability to work collaboratively with cross-functional teams.
  • Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines
  • Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done


We are an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.