Must Have Skills: • 10+ years of experience in MLOps, Data Scientist, • Solid experience working with streaming platforms: Apache Kafka, AWS Kinesis, or Spark Streaming. • Proficiency in ML libraries like scikit-learn, TensorFlow, PyTorch. • Experience with containerization (Docker) and orchestration (Kubernetes/EKS). • Familiarity with AWS services: S3, Lambda, CloudWatch, Step Functions, Glue. • Experience building and maintaining CI/CD pipelines for ML using Git, CodePipeline, or Jenkins. • deploying real-time ML models (sub-100ms latency!) on massive datasets, this is the role for you. • Build and maintain scalable MLOps pipelines using AWS SageMaker • Support full ML lifecycle: ingestion → training → versioning → deployment • Optimize models for real-time inference via APIs • Detect and address data/model drift, automate re-training workflows • Use feature stores and model registries effectively • Collaborate across data science, ML, and engineering teams • Architect end-to-end AI/ML solutions on Databricks • Hands-on with large-scale data (billions of records) • Real-time model deployment experience with <100ms latency • Familiarity with Databricks, CI/CD for ML, and monitoring • Skilled in Python, Docker, Bash, Terraform/CloudFormation