Senior Machine Learning Engineer

About the role

A leading organization is seeking a Senior Machine Learning Engineer to develop advanced AI solutions for enterprise applications. The role focuses on building intelligent AI systems, Retrieval‑Augmented Generation (RAG) architectures, semantic search, and secure on‑premise deployments.

Key responsibilities

• Develop and fine‑tune Large Language Models (LLMs) and NLP pipelines for enterprise use cases.
• Design and implement Retrieval‑Augmented Generation (RAG) architectures and semantic search solutions.
• Build forecasting, supplier risk‑scoring, anomaly detection, and optimization models.
• Deploy, optimize, and maintain machine learning models in secure on‑premise environments.
• Automate model training, deployment, and inference pipelines using MLOps practices.
• Monitor model performance, reduce inference latency, and continuously improve AI solutions.
• Collaborate with engineering and business teams to deliver production‑ready machine learning systems.

Required profile

• Minimum 5 + years of Machine Learning Engineering experience (7‑10 years preferred).
• Strong programming skills in Python.
• Hands‑on experience with PyTorch, TensorFlow, Scikit‑learn, Pandas, and NumPy.
• Experience with LLMs, Transformers, Hugging Face, LangChain, and RAG architectures.
• Proficiency in Docker, Kubernetes, MLflow, and production ML deployment.
• Experience handling structured and unstructured datasets, including SQL databases and technical documentation.

Required skills

• Python
• PyTorch
• TensorFlow
• Scikit‑learn
• Pandas
• NumPy
• Large Language Models (LLMs)
• Transformers
• Hugging Face
• LangChain
• Retrieval‑Augmented Generation (RAG)
• Docker
• Kubernetes
• MLflow
• SQL