Senior Java / Machine Learning Engineer

We’re hiring a Senior Java / ML Engineer to build intelligent systems that power demand forecasting, inventory optimization, routing, and fulfillment in a large-scale retail environment. This role bridges backend engineering and production ML, turning models into real-time decisioning systems used across distribution centers and eCommerce platforms. You’ll work with high-volume data and partner with product, data science, and operations to deliver systems that directly impact in-stock rates, delivery speed, and cost efficiency. Responsibilities

• Design and build Java-based microservices (Spring Boot) real-time inference
• Productionize ML models for forecasting, recommendations, and optimization
• Build data pipelines for training and inference (batch + streaming)

• Expose models via REST/gRPC APIs and integrate into operational systems (WMS, order routing)

• Optimize for latency, throughput, and reliability in distributed systems
• Implement monitoring (model drift, accuracy, latency, failure modes) and retraining strategies
• Partner with DS to choose between heuristics vs classical ML vs LLM/agentic approaches
• Contribute to CI/CD and DevOps for ML systems
• Participate in architecture decisions and mentor engineers

• 5-8+ years in software engineering with strong Java
• Experience with Spring Boot and microservices
• Hands-on experience integrating ML into production systems
• Strong systems design (APIs, distributed systems)
• Working knowledge of Python for ML workflows
• Solid SQL + experience with large-scale data
• Cloud experience with Google Cloud Platform, Amazon Web Services, or Microsoft Azure
• Docker + Kubernetes

• Comfortable operating in ambiguous, high-impact environments Preferred

• Experience with Kafka / PubSub
• MLOps tooling (MLflow, Vertex AI)
• Experience with forecasting, inventory, routing, or pricing
• Exposure to LLMs, RAG, or agent-based systems
• Experience in retail, supply chain, or logistics Ideal Profile A backend-heavy engineer who has successfully shipped ML-powered services and understands tradeoffs between heuristics, ML, and AI systems in real-world operations.