About the Role :

As a Lead Data Scientist, you will drive the architecture, design, and delivery of GenAI solutions, focusing on LLM and vLLM fine-tuning, data strategy, and model performance.

This is a strategic, leadership-oriented role requiring a deep technical foundation and strong stakeholder collaboration.

Key Responsibilities :

- Lead design and implementation of LLM-powered GenAI platforms and document intelligence products.

- Architect and own data pipelines for fine-tuning large language models using large-scale datasets.

- Guide and mentor data science teams on LLM training best practices, evaluation, and deployment.

- Optimize model inference (latency, throughput) using vLLM, quantization, or model distillation techniques.

- Own the model lifecycle - from experimentation to production-grade deployment.

- Partner with engineering/product teams to translate business needs into scalable AI solutions.

Required Skills :

- 7+ years in data science, with 3+ years focused on NLP and LLMs.

- Proven expertise in fine-tuning large-scale models on enterprise or open datasets.

- Hands-on with vLLM, PEFT (Parameter Efficient Fine Tuning), LoRA, and quantization strategies.

- Experience optimizing inference pipelines for production environments.

- Strong coding background in Python, PyTorch, and scalable ML architectures.

- Deep understanding of model alignment, evaluation strategies, and generative QA tasks.

Leadership Skills :

- Ability to lead cross-functional teams across data science, MLOps, and software engineering.

- Experience mentoring junior team members and reviewing model design/code.

- Strong communication skills to influence technical and non-technical stakeholders.