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Graduate Machine Learning Engineer Jobs in Texas

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Engineers on the BCI team utilize signal processing and machine learning to communicate with the brain. You will have access to the most cutting-edge neural interface hardware and develop ...

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years Department: Data Science / Engineering Employment Type: Full-time About the Role: We are looking for an ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

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 ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

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 ... Undergraduate or Graduate degree in Computer Science, Mathematics, Physics, or related fields. A ...

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 ...

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Caremark LLC, a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to Design, develop, and implement enterprise ML products and platforms for data ...

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 ...

They are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models and Mixture of Experts to lead the development and optimization of advanced AI models ...

Machine Learning Engineer

Irving, TX · On-site +1

$96K - $144K/yr

Aetna Resources, LLC., a CVS Health company, is hiring for the following role in Irving, TX: Machine Learning Engineer to build, deploy, and monitor artificial intelligence (AI)/machine learning (ML ...

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

... Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by ... Preferred Qualifications PhD or Graduate degree with research/work experience using data science ...

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 ...

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Showing results 1-20

Graduate Machine Learning Engineer information

See Texas salary details

$29.3K

$120K

$180.3K

How much do graduate machine learning engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for graduate 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 does a Graduate Machine Learning Engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

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

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

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

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

Infographic showing various Graduate Machine Learning Engineer job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $119,968 per year, or $57.7 per hour.
Machine Learning Engineer II

Machine Learning Engineer II

Yum Brands

Plano, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago


Yum! Brands rating

3.9

Company rating: 3.9 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

Hybrid onsite requirement in either Plano, TX - Irvine, CA - Louisville, KY

Company Overview:

Yum Brands is a global leader in the fast-food industry, with a portfolio of renowned brands including KFC, Pizza Hut, Taco Bell, and more. We're dedicated to providing delicious, convenient, and innovative food experiences to our customers worldwide.

Position Overview:

We are seeking a talented and passionate Machine Learning Engineer to join our dynamic team at Yum Brands. As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from customer experience optimization to supply chain management.

Qualifications:

  • Bachelor's or master's degree in computer science, engineering, mathematics, or a related field.
  • Proven experience (4+ years) in developing and deploying in production environments, preferably in the context of real-world business applications.
  • Proficiency in Python with strong software engineering skills and experience in building scalable and maintainable code.
  • Proficiency in message queue technologies and services like Kafka, Pulsar, or RabbitMQ and experience working with real-time data streaming.
  • Experience working with containerization technologies such as Docker and Kubernetes.
  • Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced and dynamic environment.

Nice to Have:

  • Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.
  • Experience with cloud computing platforms such as AWS, Azure, or GCP.
  • Experience with version control systems, such as Git.

Salary Range: 105,500 - 132,200

Benefits: Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short-term disability, long-term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off, half day Fridays year-round and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! -Click here. 

At Yum!, one of our core values is to Believe in ALL People. This means seeing the value in everyone and unlocking their full potential to be their best self. YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC ("YRSG") and Yum Connect, LLC ("Yum Digital and Technology")(collectively, "Yum") is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity.  We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.

US Job Seekers/Employees - Click here to view the "Know Your Rights" poster and supplement and the Pay Transparency Policy Statement.

Qualifications:

  • Bachelor's or master's degree in computer science, engineering, mathematics, or a related field.
  • Proven experience (4+ years) in developing and deploying in production environments, preferably in the context of real-world business applications.
  • Proficiency in Python with strong software engineering skills and experience in building scalable and maintainable code.
  • Proficiency in message queue technologies and services like Kafka, Pulsar, or RabbitMQ and experience working with real-time data streaming.
  • Experience working with containerization technologies such as Docker and Kubernetes.
  • Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
  • Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced and dynamic environment.

Nice to Have:

  • Familiarity with latest tools and trends surrounding Large Language Models and Generative AI.
  • Experience with cloud computing platforms such as AWS, Azure, or GCP.
  • Experience with version control systems, such as Git.

Key Responsibilities:

  • Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to identify opportunities for leveraging machine learning techniques to drive business outcomes.
  • Design, develop, and deploy scalable machine learning models and algorithms that address business challenges and improve operational efficiency.
  • Optimize machine learning models for performance, scalability, and efficiency.

  • Build robust data pipelines and infrastructure to support the training and deployment of machine learning models in production environments.
  • Work with DevOps teams to automate deployment processes, monitor system performance, and ensure the smooth operation of applications and services in production.
  • Stay updated on emerging technologies and industry trends in machine learning, software engineering, and cloud computing, and evaluate their potential impact on our business operations.

What Yum! Brands employees say

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