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Volunteer Machine Learning Neuroscience Jobs (NOW HIRING)

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

Machine Learning Engineers

San Jose, CA · On-site

$136K - $280K/yr

Tiktok Machine Learning Engineer (Search) - E-commerce - San JoseSan JoseRegularR DJob ID: A162279 ... As well as Dental, Vision, Short/Long Term Disability, Basic Life, Voluntary Life and AD&D ...

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... for volunteer time each calendar year. To learn more about working at Yum! -Click here. At Yum ...

WI · On-site

$105.50 - $132.20/hr

As a Machine Learning Engineer, you will play a crucial role in developing and deploying ... days for volunteer time each calendar year. Salary Range: 105,500 - 132,200 Equal Employment ...

Senior Machine Learning Engineer

$107K - $146K/yr

At Reddit, machine learning sits at the heart of how millions of people discover, connect, and ... Flexible Vacation & Paid Volunteer Time Off * Generous Paid Parental Leave

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Volunteer Machine Learning Neuroscience information

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How much do volunteer machine learning neuroscience jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for volunteer machine learning neuroscience in the United States is $28.31, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $30.53 per hour, depending on experience, location, and employer.

What cities are hiring for Volunteer Machine Learning Neuroscience jobs?

Cities with the most Volunteer Machine Learning Neuroscience job openings:

What are the most commonly searched types of Machine Learning Neuroscience jobs?

The most popular types of Machine Learning Neuroscience jobs are:

What states have the most Volunteer Machine Learning Neuroscience jobs?

States with the most job openings for Volunteer Machine Learning Neuroscience jobs include:

Infographic showing various Volunteer Machine Learning Neuroscience job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $58,889 per year, or $28.3 per hour.

Machine Learning Engineer II

Yum Brands

Plano, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 7 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.

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