Lead Machine Learning Engineer - Agentic AI

Key Responsibilities :

- Design, build, and optimize deep learning models to solve complex real-world problems.

- Work extensively with LLMs, transformer-based architectures, and advanced neural networks.

- Explore and implement modern AI capabilities including AI Agents, Agentic AI, RAG (Retrieval-Augmented Generation), Search, and Copilot-style solutions.

- Collaborate with product managers, users, and cross-functional technical teams to gather requirements and translate them into scalable solutions.

- Deploy machine learning models using Kubernetes, Docker, and cloud-native technologies.

- Conduct code reviews, maintain coding standards, and follow best practices in software development.

- Build robust workflows and pipelines for model training, testing, deployment, and monitoring.

- Stay updated with recent advancements in AI/ML research and integrate relevant innovations into existing systems.

Qualifications & Skills :

- Bachelors or Masters degree in Computer Science, Machine Learning, or a related quantitative field from a Tier 1 institution.

- 5+ years of hands-on experience in Deep Learning with a proven record of working on fast-paced technical projects.

- Proficiency in deep learning frameworks such as TensorFlow, PyTorch, and transformer-based architectures.

- Strong experience with large language models (e.g., GPT-3/4, BERT, Transformer models).

Good to have :

- Experience in AI Agents, Agentic AI systems, RAG pipelines, search applications, Copilot-style AI features.

- Familiarity with Kubernetes, Docker, and modern cloud deployment practices.

- Sound experience in software engineering practices : CI/CD pipelines, version control (Git), testing frameworks, build systems, and code reviews.

- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Attributes :

- Strong problem-solving and analytical skills.

- Passion for innovation and staying ahead of emerging AI technologies.

- Ability to work independently and collaboratively in a fast-paced environment.