Personalization Recommendation Machine Learning Jobs

We are a machine learning team focused on personalization across VIZIO’s platform. Leveraging expertise in deep learning and statistical data analysis, the group focuses on creating scalable and powerful deep learning models using frameworks like PyTorch and MLflow. Collaborating closely with cross-functional partners, the team continuously enhances model performance and deployment to deliver impactful user experiences. This environment encourages innovation, rigorous testing, and application of best practices to solve complex challenges in recommender systems and ad targeting, contributing to the platform’s growth and customer engagement. 

• Tackle ambiguous, high‑impact problems by translating product and business questions into well‑scoped ML and data science work. 

• Build, evaluate, and iterate on advanced deep learning models for personalization and recommendation. 

• Design and apply rigorous offline metrics and online experimentation frameworks to measure model and system performance. 

• Partner closely with Product and Engineering to align on scope, tradeoffs, and execution across multiple teams. 

• Help define best practices for modeling, experimentation, and ML development, with a focus on robustness and maintainability. 

• Provide technical mentorship and guidance to other data scientists through reviews, collaboration, and hands‑on problem solving. 

What you'll bring: 

• Extensive experience designing, training, and deploying machine learning models for real-world systems, particularly in personalization, recommendation, ranking, or targeting. 

• Deep technical foundations in machine learning and statistics, including experience with representation learning, deep learning architectures, optimization, and model evaluation. 

• Production Python experience, comfortable with distributed data tools such as PySpark and expertise in modern ML frameworks (e.g. PyTorch, JAX, etc.). You are opinionated about model design, training workflows, and evaluation/experimentation strategies. 

• Comfortable operating in ambiguous, technically complex problem spaces, taking ownership from initial formulation through deployment and iteration. 

• Enjoy raising the technical bar through mentorship, design reviews, and hands-on collaboration with other data scientists. 

At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. 

You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. 

For information about PTO, see https://one.walmart.com/notices. 

Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart. 

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. 

For information about benefits and eligibility, see One.Walmart. 

The annual salary range for this position is $132,000.00 - $264,000.00 

Additional compensation includes annual or quarterly performance bonuses. 

Additional compensation for certain positions may also include : 

- Stock