Description

Key Responsibilities

• Design, develop, and maintain scalable ML infrastructure and pipelines.
• Deploy, optimize, monitor, and support production machine learning systems.
• Build model-serving frameworks for recommendation and personalization platforms.
• Collaborate with Data Scientists to deploy models and ML features into production.
• Improve model performance, latency, scalability, and reliability.
• Develop solutions supporting search, recommendations, ranking, and personalization.
• Build and maintain containerized ML applications using Kubernetes.
• Implement monitoring, observability, and performance optimization strategies.
• Explore Agentic AI workflows and emerging AI technologies.

Required Qualifications

• 8+ years of experience in Machine Learning Engineering, Software Engineering, MLOps, or a related field.
• Proven experience deploying recommendation systems, search platforms, ranking engines, or personalization solutions into production.
• Strong Python programming skills.
• Experience building ML pipelines, model-serving frameworks, and scalable production systems.
• Strong experience with Google Cloud Platform (GCP).
• Hands-on experience with Vertex AI and Vertex Search.
• Experience with Kubernetes and containerized deployments.
• Expertise in model deployment, optimization, tuning, monitoring, and production support.
• Experience scaling ML solutions from proof of concept to enterprise-level production.
• Strong communication, problem-solving, and collaboration skills.

Preferred Qualifications

• Experience in grocery, retail, e-commerce, marketplaces, or consumer technology.
• Experience with LangSmith for AI application observability and evaluation.
• Familiarity with Agentic AI workflows and AI orchestration frameworks.
• Experience with search, retrieval, ranking, recommendation, or personalization systems.
• Experience supporting large-scale, customer-facing ML platforms.

Key Skills

Education

Bachelor's degree