Sr ML Engineer

Responsibilities :

• Build and manage end-to-end ML pipelines using Vertex AI Pipelines , Airflow , or similar orchestrators.
• Implement ML models using TensorFlow , PyTorch , or other frameworks; monitor model performance in production.
• Manage Python environments using venv , pip , poetry , and containerized deployments with Docker .
• Design and implement distributed data pipelines with Apache Spark , Beam , or Flink .
• Develop data ingestion workflows from databases and API-based sources using GCP tools .
• Optimize pipelines and clusters for performance, cost, and scalability.
• Perform feature engineering, data engineering, and ML model evaluation.
• Develop and maintain CI / CD pipelines , deployment strategies, and infrastructure-as-code using Terraform .
• Design data architecture considering storage and compute options for efficient BI and analytics use cases.
• Optional / Good to have : Kubernetes, Vector Databases (e.g., Qdrant), and LLM experience (embeddings, RAG, agents).

Skills Required

Python, Java, Machine Learning, Tensorflow, Pytorch, Docker