Description

You will own the development and deployment of AI/ML systems.

Responsibilities

• Design, build, and optimize machine learning models for prediction, classification, and NLP tasks.
• Develop end-to-end ML pipelines covering training, validation, and evaluation.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines using LLMs.
• Deploy ML models into production using scalable microservices and APIs.
• Design ML system architecture for high-volume, low-latency environments.

Required Skills

• 10+ years of professional experience in AI/ML engineering.
• Strong proficiency in Python.
• Hands-on experience with PyTorch, TensorFlow, and Scikit-learn.
• Expertise in Deep Learning, Feature Engineering, and Model Optimization.
• Experience with transformer models and LLM APIs.
• Proficiency in prompt engineering, embeddings, and vector databases (e.g., FAISS, Pinecone, Chroma).
• Experience with MLFlow, Kubeflow, or Airflow for pipeline management.
• Familiarity with Docker and Kubernetes for deployment.
• Hands-on experience with at least one major cloud platform: GCP, AWS, or Azure.

Preferred Skills

• Experience with Hugging Face.
• Knowledge of CI/CD practices for ML pipelines.

Key Skills

Education

Any Gradute