MLOps Engineer (Java)

Key Responsibilities:

Design and implement scalable model serving platforms for both batch and real-time inference

Build model deployment pipelines with automated testing and validation

Develop monitoring, logging, and alerting systems for ML services

Create infrastructure for A/B testing and model experimentation

Implement model versioning and rollback capabilities

Design efficient scaling and load balancing strategies for ML workloads

Collaborate with data scientists to optimize model serving performance Technical Requirements:

7+ years of software engineering experience, with 3+ years in ML serving/infrastructure

Strong expertise in container orchestration (Kubernetes) and cloud platforms

Experience with model serving technologies (TensorFlow Serving, Triton, KServe)

Deep knowledge of distributed systems and microservices architecture

Proficiency in Java and experience with high-performance serving

Strong background in monitoring and observability tools

Experience with CI/CD pipelines and GitOps workflows