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Machine Learning Developer Jobs in Texas (NOW HIRING)

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 ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137.30K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

Photon

Machine Learning Engineer - NJ

Addison, TX · On-site

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Photon

Machine Learning Engineer - NJ

Addison, TX

$54 - $71.50/hr

We are seeking a Machine Learning Engineer to design and develop robust analytics models using statistical and machine learning algorithms. In this role, you will work closely with product and ...

Apple

Senior Machine Learning Engineer

Austin, TX · On-site

$121.40K - $160.10K/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 ...

Striveworks

Senior Machine Learning Engineer

Austin, TX · On-site +1

$121.40K - $160.10K/yr

... and DevOps engineers to transform machine learning models into operational capabilities. You're right for this opportunity if you value and possess technical expertise and enjoy pushing the ...

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Machine Learning Developer information

See Texas salary details

$17

$35

$48

How much do machine learning developer jobs pay per hour?

As of May 29, 2026, the average hourly pay for machine learning developer in Texas is $35.79, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $48.37 per hour, depending on experience, location, and employer.

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

To excel as a Machine Learning Developer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or related fields. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, as are certifications in data science or AI. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data findings into actionable solutions. These skills and qualities are essential to develop accurate models, collaborate with stakeholders, and drive innovation in a rapidly evolving field.

What are some common challenges faced by Machine Learning Developers when deploying models to production environments?

Machine Learning Developers often encounter challenges such as ensuring model scalability, managing data drift, and integrating models with existing systems during deployment. Another frequent hurdle is monitoring model performance in real time and retraining models as new data becomes available. Collaborating closely with data engineers, DevOps, and software developers is essential to streamline the deployment pipeline and maintain model reliability in production.

What does a Machine Learning Developer do?

A Machine Learning Developer designs, builds, and implements machine learning models and systems that enable computers to learn from data without explicit programming. They work with large datasets, select appropriate algorithms, and optimize models for various tasks such as predictions, classifications, and recommendations. Their responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models into production environments. Machine Learning Developers typically collaborate with data scientists, software engineers, and business teams to deliver AI-powered solutions.

What is the difference between Machine Learning Developer vs Data Scientist?

AspectMachine Learning DeveloperData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications like TensorFlow or AWS MLBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops and deploys ML models in software or cloud environmentsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, predictive modeling, and insights

Both roles require strong programming skills and knowledge of ML algorithms. Machine Learning Developers focus on building and deploying models in production environments, while Data Scientists analyze data to inform business decisions. The roles often overlap but differ mainly in their primary focus and end goals.

What are popular job titles related to Machine Learning Developer jobs in Texas? For Machine Learning Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Developer jobs in Texas look for? The top searched job categories for Machine Learning Developer jobs in Texas are:
Machine Learning Developer jobs near you
Infographic showing various Machine Learning Developer job openings in Texas as of May 2026, with employment types broken down into 60% Full Time, 16% Part Time, 18% Contract, 3% Nights, and 3% Summer. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution, with an average salary of $74,449 per year, or $35.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Q2

Austin, TX • Hybrid

Full-time

Medical

Posted 5 days ago

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

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About Q2

Sourced by ZipRecruiter

Industry

Finance and insurance

Company size

1,001 - 5,000 Employees

Headquarters location

Austin, TX, US

Year founded

2004

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