Website:
anjusmriti.com
Job details:
Responsibilities-
· Build and automate ML workflows using Apache Airflow / Cloud Composer for data ingestion, preprocessing, and model training.
· Manage MLflow for experiment tracking, model packaging, versioning, and Model Registry.
· Develop and optimize training environments for ML/LLM workloads.
· Design scalable model-serving solutions using FastAPI/Flask, API Gateway, and high-performance inference endpoints.
· Manage Docker and Kubernetes/GKE infrastructure, including auto-scaling GPU/CUDA workloads.
· Implement CI/CD pipelines and automate ML application delivery.
· Monitor model performance, latency, data drift, and infrastructure health.
· Work with Vertex AI services including Workbench, Model Garden, Feature Store, Vertex AI Pipelines, and BigQuery ML.
· Use Terraform to create and maintain reproducible cloud infrastructure.
· Develop production-quality Python code with testing and modular design.
· Work with CDC, Spark/PySpark, and optimize data movement between BigQuery and training environments.
· Implement secure ML environments using IAM, VPC Service Controls, and endpoint security practices.
Key Skills
· 3–5 years of relevant MLOps / ML Engineering experience.
· Strong Python, Docker, Kubernetes, GKE/AKS, and Terraform.
· Hands-on Airflow / Cloud Composer and MLflow experience.
· Experience with GCP, Azure, Vertex AI, BigQuery ML, and Vertex AI Pipelines.
· Knowledge of Kubernetes operators and resource management for ML workloads.
· Experience with FastAPI/Flask, API Gateway, CI/CD, and ML model serving.
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