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Google Machine Learning Engineer Jobs in Texas (NOW HIRING)

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 ...

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 ...

Google Machine Learning Engineer,Data Engineer,Google Cloud ProfessionalArchitect,or other relevant Google Cloud certifications are highly preferred;Other AI-relatedCertifications are a plus * Deep ...

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 ...

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 ...

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 ...

Showing results 21-40

Google Machine Learning Engineer information

What are the key skills and qualifications needed to thrive in the Google Machine Learning Engineer position, and why are they important?

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What is a Google Machine Learning Engineer job?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

What types of projects and collaborations can Google Machine Learning Engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Texas? The most popular types of Google Machine Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Google Machine Learning Engineer jobs? Cities in Texas with the most Google Machine Learning Engineer job openings:
Infographic showing various Google Machine Learning Engineer job openings in Texas as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Machine Learning Engineer II

Machine Learning Engineer II

Yum Brands

Plano, TX

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Yum! Brands rating

5.4

Company rating: 5.4 out of 10

Based on 13 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

Pay

Benefits

Hours and flexibility

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