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Machine Learning Engineer Biotech Jobs in Austin, TX

Machine Learning Engineer

Austin, TX ยท On-site

$140K - $180K/yr

๐Ÿš€ Machine Learning Engineer ๐Ÿ“ Austin, TX (Hybrid/Remote Considered) ๐Ÿ’ฐ $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

They are seeking an experienced Machine Learning Engineer to develop and deploy machine learning solutions for autonomous systems, focusing on model optimization and data management. Responsibilities ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

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

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data ...

About the role We are looking for an experienced Machine Learning Engineer with a strong background in developing and deploying modern machine learning solutions for complex real-world challenges. In ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions, while collaborating with cross-functional teams to advance machine learning ...

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

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

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

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance ...

Machine Learning Engineer

Austin, TX ยท On-site

$199K - $331K/yr

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

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Showing results 1-20

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 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:
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.

Machine Learning Engineer

X4 Engineering

Austin, TX โ€ข On-site

$140K - $180K/yr

Other

Posted 10 days ago


Job description

๐Ÿš€ Machine Learning Engineer

๐Ÿ“ Austin, TX (Hybrid/Remote Considered)

๐Ÿ’ฐ $140,000 - $180,000 Base


We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to join a highly technical platform engineering team supporting traders, analysts, and quantitative researchers.


This is not a pure data science role. We're looking for an engineer who enjoys building robust production systems, scaling data and ML infrastructure, and working closely with front-office stakeholders to deliver real business impact.


What you'll be doing:

  • Building and maintaining ML and data platforms used for forecasting, optimization, and trading workflows
  • Designing scalable cloud-native infrastructure and deployment pipelines
  • Productionizing quantitative models and analytics tools
  • Developing distributed data and compute systems
  • Working directly with traders and business users to deliver reliable solutions
  • Driving engineering best practices across CI/CD, observability, testing, and automation


Tech stack includes:

Python | AWS | Kubernetes | Docker | Terraform | Airflow | Spark | MLflow | Databricks | Kafka | CI/CD

We're interested in people from backgrounds such as:

โœ” Machine Learning Engineering

โœ” MLOps Engineering

โœ” Platform Engineering

โœ” Software Engineering (with ML/Data exposure)

โœ” Quant Development

โœ” Infrastructure Engineering


Ideal candidates will have strong Python skills, cloud and DevOps experience, and a track record of building production systems. Experience within energy, trading, forecasting, or quantitative environments is beneficial but not essential.


If you'd like to learn more, please send me a message or apply directly.


They prefer the role to be worked on a hybrid model of 1-2 days a week. Salary offered is $140,000-$180,000.