AIML GCP Engineer

Job Requirements Translate data science prototypes into production-grade ML services and pipelines.Build training and inference code with reproducibility, versioning, and automated testing.Implement scalable model serving (online/offline), batching, and latency/throughput optimization.Integrate model lifecycle tooling (tracking, registry, deployment automation, monitoring).Collaborate with Data Engineering on feature pipelines and data contracts.Own production health: drift detection, performance regression, rollback strategies, and incident response.""- 5+ years software engineering with 2+ years shipping ML models to production.Strong Python skills and experience with ML frameworks (TensorFlow/PyTorch).Experience with containers and orchestration (Docker/Kubernetes) and API development.Understanding of ML system design (data leakage, training-serving skew, drift).CI/CD and DevOps practices applied to ML workloads (MLOps).""- Experience with feature stores, model registries, and model monitoring stacks.GPU optimization and distributed training experience.Experience with responsible AI toolkits and compliance requirements."Python, TensorFlow, PyTorch, Docker, REST APIsWork Experience 2-5YearsJob SummaryJob number: P-102861Profession: OtherExperience: 2-5Years