Tech Stack

Description

You will design end-to-end AI/ML architectures, lead technical evaluations, and define best practices for responsible AI. You'll provide expert guidance across the full ML lifecycle, support LLM-based applications and RAG systems, and mentor engineers to elevate technical excellence.

Requirements

• 7+ years in data science, machine learning, or AI engineering
• 3+ years in a senior or principal-level architectural role
• Strong proficiency in Python and ML/AI frameworks (TensorFlow, PyTorch, Scikit-Learn, transformers)
• Hands-on experience with cloud AI services (AWS Sagemaker, Azure ML, GCP Vertex AI) and data engineering tools (Spark, Databricks, Airflow, Kafka)
• Experience with LLM architectures, fine-tuning, embeddings, vector stores (FAISS, Pinecone, Weaviate), and MLOps (MLflow, Kubeflow, DVC, CI/CD)

Responsibilities

• Design end-to-end AI/ML architectures including data ingestion pipelines, feature stores, model training, deployment, and monitoring
• Lead evaluation and selection of AI/ML tools, frameworks, cloud components, and platforms
• Define standards, best practices, and governance frameworks for responsible AI usage
• Partner with product and engineering leadership to shape long-term AI roadmap
• Oversee technical design of AI projects, ensuring quality, reliability, and security