Senior Java / Machine Learning Engineer

Marathon TS

$100K — $140K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-8+ years in software engineering with strong Java expertise
  • Experience with Spring Boot and building microservices
  • Hands-on integration of ML models into production environments
  • Strong design skills in APIs and distributed systems
  • Proficient in SQL with experience handling large-scale datasets
  • Familiar with cloud platforms such as GCP, AWS, or Azure
  • Experience with Docker and Kubernetes for container management

Responsibilities

  • Design and build real-time inference microservices using Java and Spring Boot
  • Productionize machine learning models for various optimization tasks
  • Develop data pipelines for ML training and inference processes
  • Create REST/gRPC API endpoints and integrate them into existing operational systems
  • Optimize distributed systems for performance metrics like latency and throughput
  • Implement monitoring strategies for model performance and reliability
  • Collaborate with data scientists to determine appropriate ML techniques and algorithms

Benefits

  • Opportunity to work in a large-scale retail environment
  • Engagement with cross-functional teams including product, data science, and operations
  • Influence on architecture decisions and mentoring opportunities
  • Exposure to advanced technologies and techniques in machine learning and operational optimization
  • Dynamic and high-impact work setting
Full Job Description
Title: Senior Java / Machine Learning Engineer (Supply Chain & Fulfillment)
Overview
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
Required
• 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.

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