Staff ML Engineer: Lead Scalable AI & LLM Systems

Walmart; Bentonville (AR); On-site; USD 130,000 - 260,000; Full time

Benefits offered by this job

Health benefits

401(k)

Stock purchase plan

Company-paid life insurance

PTO & holidays

Live Better U education benefit

Job summary

Walmart Data Ventures seeks a Staff Machine Learning Engineer to design and deploy scalable, production-grade ML/AI systems across cloud environments. You will own the ML lifecycle, guide architecture decisions, mentor teams, and drive continuous improvement through AutoML, NLP, and robust observability.

You will translate business problems into technical requirements, ensure low latency and high reliability, and lead cross-functional collaboration with software, data science, and product teams.

Qualifications

• Bachelor's degree in computer science, computer engineering, software engineering, or related field or 6 years of software/ML experience.
• Extensive experience designing and operating large-scale ML systems across training, evaluation, batch and real-time inference.
• Strong understanding of MLOps, distributed systems, cloud-native architectures, APIs, containers, and data platforms.

Responsibilities

• Lead design and delivery of scalable, production-grade ML and AI systems.
• Translate business problems into technical requirements, architectures, and success criteria.
• Productionize DS prototypes across batch, real-time, and agentic workloads.
• Own ML lifecycle, SDLC, CI/CD, versioning, testing, deployment, evaluation, observability, and monitoring.

Skills

Python

SQL

System design

CI/CD

Production ops

MLOps

LLM/agentic systems

Education

B.S. in CS/Engineering or related

Master’s degree preferred

Tools

TensorFlow

PyTorch

Kubernetes

Docker

MLflow

Job description

Walmart Data Ventures seeks a Staff Machine Learning Engineer to design and deploy scalable, production-grade ML/AI systems across cloud environments. You will own the ML lifecycle, guide architecture decisions, mentor teams, and drive continuous improvement through AutoML, NLP, and robust observability.

You will translate business problems into technical requirements, ensure low latency and high reliability, and lead cross-functional collaboration with software, data science, and product teams.