ZipRecruiter

Log In

1

Machine Learning Engineer Opt 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 · 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 ...

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 ...

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Texas

Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
What are popular job titles related to Machine Learning Engineer Opt jobs in Texas? For Machine Learning Engineer Opt jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Texas look for? The top searched job categories for Machine Learning Engineer Opt jobs in Texas are:
What cities in Texas are hiring for Machine Learning Engineer Opt jobs? Cities in Texas with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Texas as of May 2026, with employment types broken down into 95% Full Time, 2% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.

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

Apply