Job Description:

We are seeking a highly skilled and versatile Machine Learning Engineer (with GenAI expertise) who combines strong software engineering fundamentals with deep experience in machine learning and modern Generative AI systems. The ideal candidate will design, develop, and maintain scalable AI-powered applications using Python, with a strong emphasis on Object-Oriented Programming principles.

You will play a key role in building end-to-end AI systems, including LLM-powered applications, Retrieval-Augmented Generation (RAG) pipelines, and agent-based workflows, alongside traditional ML models. This role demands strong analytical thinking, coding expertise, architectural design skills, and a deep

understanding of the full ML and GenAI lifecycle—from data processing and model development to deployment, monitoring, and optimization.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, AI, ML, Data Science, or related field.

• 5years of experience in AI/ML engineering, with 2–3 years in a lead role.

• Strong expertise in Python, system design,



and scalable AI/ML architecture.

• Hands-on experience with TensorFlow, PyTorch, and Scikit-learn.

• Solid knowledge of NLP, Computer Vision, Generative AI, LLMs, and deep learning models.

• Experience with Docker, Kubernetes, MLOps, CI/CD, and cloud platforms like Amazon Web Services,

Google Cloud Platform, or Microsoft Azure.

• Strong leadership, stakeholder management, and team mentoring skills.

Key Responsibilities:

• Core ML & Engineering

• Write clean, efficient, and well-documented Python code following OOP principles (encapsulation,

inheritance, polymorphism, abstraction).

• Build and manage end-to-end ML pipelines: data ingestion, preprocessing, model training,

evaluation, and deployment.

• Develop scalable ML systems using frameworks like PyTorch, TensorFlow, and Scikit-learn.

• Generative AI (GenAI) & LLM Systems

• Design and implement LLM-based applications (chatbots, c

📌 AI/ML Engineer (Gurugram)
🏢 Antino
📍 Gurugram