(USA) Staff, Machine Learning Engineer

Overview In this role you will lead the design and deployment of scalable production ML solutions that address critical business needs. You will own the full ML lifecycle and set technical standards across teams, driving experimentation and innovation. You’ll build reusable ML infrastructure and apply MLOps best practices to ensure reliability at scale. You’ll mentor engineers, collaborate across Product, Data, and Platform groups, and help Walmart advance its AI capabilities to deliver measurable business impact. Compensation / Benefits Health benefits: medical, vision, dental 401(k) and stock purchasecompany-paid life insurance Paid time off including PTO and sick leave Parental, family care, bereavement leaves Disability coverage and other perks Responsibilities Design and deploy scalable, production-grade ML solutions Oversee end-to-end ML lifecycle: data sourcing, feature engineering, training, deployment, monitoring Implement MLOps practices: CI/CD, model versioning, telemetry-based monitoring Build and maintain ML infrastructure for large-scale cloud operations (containers, Kubernetes, workflow automation)Provide technical leadership, code quality, testing, and deployment standards Drive experimentation pipelines and explore advanced ML techniques Mentor engineers and enforce engineering standards Collaborate across teams and stakeholders to align with business objectives Key requirements Proven experience delivering scalable ML solutions aligned with business needs Strong proficiency in Tensor Flow, PyTorch, Scikit-learn and Python/SQLExperience with end-to-end ML lifecycle management and monitoring Knowledge of MLOps practices: CI/CD, model versioning, telemetry Familiarity with AWS, GCP, Azure, containerization, Kubernetes, and workflow automation Ability to implement robust model evaluation and validation frameworks Demonstrated leadership and mentorship of engineers Strong collaboration and communication skillscollaborationcommunicationleadership Tensor Flow PyTorch Scikit-learn