Senior, Software Engineer (Machine Learning)

Position Summary...

What you'll do...

As a Senior Machine Learning Engineer, you are a technical leader working at the intersection of machine learning and software engineering. You have expertise in both areas and are responsible for the full lifecycle of complex machine learning systems – from initial ideas and design to deployment, monitoring, and updates. This role requires strong technical skills, strategic planning, system design ability, and mentorship.

Senior Engineers don't just implement existing plans; they define the technical approach and architecture for systems. You will be important in setting and promoting best practices, guiding technical direction in your area, and possibly contributing to the overall engineering strategy. While your specific focus might align with roles like a Tech Lead guiding a team, an Architect defining a critical technical area, or a Solver tackling high-risk problems, the core elements are technical leadership, system-level thinking, and broad impact. You will balance hands-on work with system design and technical guidance.
 

About Team:  
Our eCommerce Search team is an integral part of Walmart International, which encompasses over 5,200 retail units across 23 countries, including Canada, Central America, Chile, Mexico, and South Africa. We are dedicated to building a cutting-edge machine learning platform that addresses the diverse needs of customers, associates, and the business. Our mission is to enhance the shopping experience for millions of customers worldwide by leveraging advanced technologies and innovative solutions.

What you’ll do:

• End-to-End ML System Development: Lead the design, development, implementation, testing, and deployment of reliable and scalable machine learning systems and infrastructure. This includes building and optimizing components such as model training and validation workflows, and efficient model serving systems. You will contribute to the system lifecycle, ensuring its reliability and maintainability.

• Technical Contribution & Guidance: Contribute to the definition of the technical strategy and system architecture for significant machine learning projects. Provide technical guidance and mentorship to other engineers on the team, promoting engineering best practices. You will participate in making key design decisions, considering trade-offs like complexity, performance, cost, and maintainability.

• Software Engineering Proficiency: Apply strong software engineering practices throughout the ML development process. Promote and utilize practices for writing clean, modular, tested, and maintainable code. Utilize best practices for version control (Git), automated testing, and continuous integration and deployment.

• Collaboration & Communication: Effectively collaborate with cross-functional teams, including product managers, data scientists, and other engineers, to understand requirements and deliver impactful solutions. Clearly communicate technical concepts and project progress to both technical and non-technical stakeholders.

• Troubleshooting business and production issues by reviewing and analyzing information (for example, issue, impact, criticality, possible root cause); engaging support teams to assist in the resolution of issues; formulating an action plan; directing actions as designated in the plan; interpreting the results to determine further action; performs root cause analysis to prevent future occurrence of issues; and completing online documentation.

What you’ll bring:

• Large-Scale Data Platforms: Experience with distributed data processing tools like Apache Spark and cloud data platforms like Snowflake or Databricks.

• MLOps Tooling: Experien