Applied Scientist - Recommender Systems & RL (Onsite)

Socket.dev; Sunnyvale (CA); On-site; USD 143,000 - 286,000; Full time

Benefits offered by this job

401(k) match

Stock purchase plan

Paid leave

Job summary

Walmart Global Tech is seeking a highly skilled Applied Scientist experienced in recommender systems, information retrieval, and reinforcement learning to invent scalable solutions for Walmart’s marketplace goals. The role requires creating production-grade ML models and working across teams in a fast-moving environment.

The successful candidate will leverage LLMs, deep learning, and advanced statistical models to deliver measurable customer impact, with on-site work in Sunnyvale, CA.

Qualifications

• PhD with 2+ years or MS with 5+ years in CS/ML or related field.
• Experience implementing and scaling production-grade ML models.
• Strong background in RL, contextual bandits, or related optimization methods.

Responsibilities

• Map product and business requirements to ML/AI problems.
• Design and implement scalable ML models for recommender systems and other scalable models.
• Analyze large datasets to derive actionable insights; build robust ML systems with LLMs and deep learning.
• Collaborate across teams in a fast-moving environment to achieve business goals.

Skills

Recommender systems

Information retrieval

Reinforcement learning

Java

Python

PySpark

TensorFlow

PyTorch

Education

PhD with 2+ years or MS with 5+ years in CS/ML

Tools

TensorFlow

PyTorch

Job description

Walmart Global Tech is seeking a highly skilled Applied Scientist experienced in recommender systems, information retrieval, and reinforcement learning to invent scalable solutions for Walmart’s marketplace goals. The role requires creating production-grade ML models and working across teams in a fast-moving environment.

The successful candidate will leverage LLMs, deep learning, and advanced statistical models to deliver measurable customer impact, with on-site work in Sunnyvale, CA.