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Machine Learning Engineer Biotech Jobs in Austin, TX

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 ...

Senior Machine Learning Engineer

Austin, TX ยท On-site +1

$335K - $400K/yr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Senior Machine Learning Engineer

Austin, TX ยท On-site

$335K - $400K/yr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Senior Machine Learning Engineer

Austin, TX ยท On-site

$335K - $400K/yr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

Machine Learning Engineer, Senior

Austin, TX ยท 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.

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 ...

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 ...

Senior Machine Learning Engineer

Austin, TX ยท 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 ...

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 ...

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 ...

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 ...

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 ...

We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track ...

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data ...

Showing results 21-40

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 24, 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 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 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 July 2026, with employment types broken down into 87% Full Time, 6% Part Time, 1% Temporary, and 6% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $127,637 per year, or $61.4 per hour.
Machine Learning Engineer

Machine Learning Engineer

Q2

Austin, TX โ€ข Hybrid

Full-time

Medical

Posted yesterday


Job description

As passionate about our people as we are about our mission.

Why Join Q2?

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs in the U.S. and internationally. Our mission is simple: build strong and diverse communities through innovative financial technology-and we do that by empowering our people to help create success for our customers.

What Makes Q2 Special?

Being as passionate about our people as we are about our mission. We celebrate our employees in many ways, including our "Circle of Awesomeness" award ceremony and day of employee celebration among others! We invest in the growth and development of our team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun. We hold an annual Dodgeball for Charity event at our Q2 Stadium in Austin, inviting other local companies to play, and community organizations we support to raise money and awareness together.

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-to-end AI solution patterns involving LLMs, APIs, RAG, vector search, intelligent agents, orchestration workflows, Snowflake, cloud platforms such as AWS and Azure, and enterprise data integration. The role partners across data, engineering, business applications, operations, IAM, and governance teams to create reusable frameworks that accelerate delivery while supporting security, access controls, compliance, and audit needs. This position may require minimal travel for collaboration, planning, or stakeholder engagement.

Responsibilities
  • Design enterprise solution patterns that align business needs with scalable implementation approaches.

  • Collaborate with cross-functional teams to translate business challenges into structured architecture recommendations.

  • Identify, analyze, and resolve gaps related to scalability, data readiness, interoperability, and operational adoption.

  • Define reusable frameworks and standards that improve delivery consistency across teams and use cases.

  • Evaluate solution options, assess trade-offs, and provide recommendations that balance performance, cost, risk, and business value.

  • Guide teams through architecture decisions that support responsible adoption and long-term maintainability.

  • Influence organizational direction by promoting best practices, shared patterns, and practical governance approaches.

  • Stay current on emerging practices and assess their applicability to enterprise priorities.

Experience and Knowledge

  • 5-8 years of relevant professional experience in engineering, architecture, data, or enterprise technology roles

  • Bachelor's degree in a relevant field.

  • Strong understanding of enterprise architecture principles, system design, integration patterns, and scalable delivery models.

  • Experience partnering with business and technical stakeholders to define practical solutions for complex organizational needs.

  • Ability to evaluate ambiguous problems, structure recommendations, and communicate trade-offs clearly.

  • Demonstrated judgment in balancing innovation, security, governance, cost, and operational feasibility.

  • Strong collaboration skills with the ability to influence across teams without direct authority.

  • Working knowledge of responsible technology adoption, risk management, and enterprise control environments.

This position requires fluent written and oral communication in English.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

Health & Wellness

  • Hybrid Work Opportunities

  • Flexible Time Off

  • Career Development & Mentoring Programs

  • Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents

  • Community Volunteering & Company Philanthropy Programs

  • Employee Peer Recognition Programs - "You Earned it"

Click here to find out more about the benefits we offer.

Our Culture & Commitment:

We're proud to foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. And our benefits go beyond healthcare-offering resources for physical, mental, and professional well-being. Click here to find out more about the benefits we offer. Q2 employees are encouraged to give back through volunteer work and nonprofit support through our Spark Program (see more). We believe in making an impact-in the industry and in the community.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status.


Applicants in California or Washington State may not be exempt from federal and state overtime requirements


Q2 logo

About Q2

Sourced by ZipRecruiter

Industry

Finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Austin, TX, US

Year founded

2004