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Machine Learning Engineer Jobs in Texas (NOW HIRING)

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 ...

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 ...

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 ...

Chevron

Lead Machine Learning Engineer

Houston, TX

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that drive critical decisions across subsurface and wells operations. In this role, you will partner with ...

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 ...

Chevron

Lead Machine Learning Engineer

Houston, TX · On-site

$97K - $128K/yr

Chevron is seeking a Machine Learning Engineer to build and scale production AI solutions that drive critical decisions across subsurface and wells operations. In this role, you will partner with ...

K-Tek Resourcing LLC

Sr. Machine Learning Engineer

Austin, TX · On-site

$113K - $136K/yr

Don'''''t apply OPT holder, please Machine Learning Engineer Responsibilities * Design, develop, train, and deploy machine learning models to solve business problems. * Build and maintain scalable ...

Bespoke Labs

Machine Learning Engineer

Arlington, TX · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Austin, TX · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Dallas, TX · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Mckinney, TX · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

San Marcos, TX · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Laredo, TX · On-site

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 ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Texas

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 28, 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.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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.

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 June 2026, with employment types broken down into 1% As Needed, 93% Full Time, 3% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.
Machine Learning Engineer

Machine Learning Engineer

Tiger Analytics Inc.

Plano, TX • On-site

Full-time

Posted 14 days ago

Job description

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 Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

Requirements


We are looking for an experienced AI/ML Lead with deep expertise in designing and deploying high-performance APIs and microservices on AWS Fargate (ECS). The ideal candidate will have hands-on experience in generative AI integration, LLM API development, and AWS Bedrock services, contributing to building scalable GenAI and Agentic AI applications.

Key Responsibilities:
  • Design, build, and optimize high-performance APIs and microservices using Python (Fast API) deployed on AWS Fargate (ECS).
  • Integrate LLM and Generative AI APIs using providers such as AWS Bedrock, OpenAI, and others.
  • Collaborate with ML and DevOps teams to design CI/CD and MLOps pipelines within the AWS ecosystem.
  • Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems.
  • (Preferred) Leverage familiarity with Bedrock Agent Core services to integrate intelligent agent capabilities.
  • Develop and maintain JSON RESTful APIs, adhering to OpenAI API conventions and best practices.
Required Skills & Experience:
  • 5+ years of hands-on software development experience with Python.
  • Proven expertise in FastAPI and microservice architecture.
  • Strong understanding of cloud-native applications, container orchestration (ECS, Docker), and AWS tools.
  • Proficiency in LLM API integration and working with Generative AI frameworks.
  • Experience implementing CI/CD, IaC, and ML pipelines across AWS environments.
  • Familiarity with Bedrock AgentCore or other agentic systems (nice to have).
Why Join Us:

You’ll be part of an innovative team building the next generation of AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries in Agentic AI infrastructure development in a supportive, fast-moving environment.

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.