Description :

We are looking for a visionary Lead Machine Learning Engineer to spearhead the development and deployment of our next-generation generative AI features.

This role is focused on leveraging Large Language Models (LLMs) and other generative models to create innovative user experiences and internal tools.

You will lead a small team, own the ML lifecycle, and drive research into production.

Key Responsibilities :

- Model Development : Design, train, fine-tune, and evaluate state-of-the-art Generative AI models (e.g., Llama, GPT variants, Diffusion Models) for specific product use cases.

- MLOps Pipeline : Build and maintain scalable, production-ready MLOps pipelines for continuous training, deployment, and monitoring of models.

- Research & Innovation : Stay abreast of the latest advancements in LLMs, prompt engineering, and RAG (Retrieval-Augmented Generation) techniques, and drive adoption.

- System Integration : Collaborate with backend and product teams to integrate models as services using APIs (e.g., FastAPI/Flask) ensuring low-latency inference.

- Mentorship : Provide technical leadership and mentorship to junior ML engineers and data scientists.

Required Skills :

- Strong background in deep learning frameworks like PyTorch or TensorFlow.

- Demonstrated experience with Generative AI models and transformers.

- Proficiency in MLOps tools (e.g., MLflow, Kubeflow, Sagemaker).

- Expertise in Python and standard data science libraries (Pandas, Scikit-learn).

- Experience with vector databases (e.g., Pinecone, Weaviate) and RAG architecture is a plus