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Machine Learning Engineer Jobs in Texas (NOW HIRING)

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 ...

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 ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Samprasoft

US|Machine Learning Engineer V

Houston, TX · On-site

Machine Learning Engineer Responsibilities: Develop machine learning workflows to enable an Azure-First approach to computer vision applications. Conduct POCs with different vendors in data science ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

SynergisticIT

Machine learning engineer

Austin, TX

Currently, we are looking for entry-level software programmers, IT enthusiasts, Python/Java ... NLP, Deep Learning, Data visualization, Scala, Django. Our candidates always get projects with well ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/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 ...

Tiger Analytics

Machine Learning Engineer

Plano, TX

Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine ...

Indeed

Senior Machine Learning Engineer

Austin, TX

$103K - $142K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

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Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

How much do machine learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer in Texas is $119,968.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,600.00 and $144,400.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Texas? The most popular types of Machine Learning Engineer jobs in Texas are:
What are popular job titles related to Machine Learning Engineer jobs in Texas? For Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Texas look for? The top searched job categories for Machine Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Machine Learning Engineer jobs? Cities in Texas with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in TX? For Machine Learning Engineer jobs in TX, the most frequently searched job titles are:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Texas as of May 2026, with employment types broken down into 1% Internship, 56% Full Time, 41% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.

Machine Learning Engineer

Q2 Software, Inc.

Austin, TX • On-site

Full-time

Medical

Posted 14 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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