Lead AI / ML Engineer

About the Role

Architect scalable ML pipelines, services, and platforms using modern cloud and MLOps practices.

Responsibilities

Build, fine-tune, and integrate Generative AI models (LLMs, Vision Models, Multimodal Models) into business applications.

Work with agentic AI frameworks to design autonomous and semi-autonomous AI agents.

Collaborate with cross-functional stakeholders to translate business needs into AI-driven solutions.

Review code, guide junior engineers, and ensure best practices in model development and deployment.

Evaluate new tools, frameworks, and approaches to keep the AI ecosystem cutting-edge.

Qualifications

8–10 years of hands-on experience in Machine Learning, Deep Learning, and AI Engineering.

Prior experience architecting AI / ML systems, including solution design, model lifecycle management, and scalability considerations.

Required Skills

Strong expertise in : Python, ML frameworks (TensorFlow / PyTorch)

Model training, optimization, and evaluation

Data engineering concepts & ML pipeline automation

Deep understanding of GenAI, including LLMs, prompt engineering, fine-tuning, embeddings, vector DBs, and RAG.

Hands-on experience with agentic AI frameworks (LangChain, AutoGen, LlamaIndex, or similar).

Cloud experience (AWS, Azure, or GCP) with MLOps tools such as SageMaker, Vertex AI, MLflow, Kubeflow, etc.

Strong problem-solving abilities with the ability to convert business challenges into AI-based solutions.