Lead Data Scientist

Lead the design and deployment of enterprise-grade generative AI systems, driving innovation in LLM orchestration, multimodal architectures, and scalable AI / ML pipelines. Own the full lifecycle from research to production, ensuring alignment with business objectives and ethical AI standards. This will be a hands-on individual contributor role as well as providing technical guidance to junior developers.

Key Responsibilities

• Technical Leadership
• Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for cost-performance optimization.
• Design GPU / TPU-optimized training pipelines (FSDP, DeepSpeed) for billion-parameter models.
• Cloud-Native AI Development
• Build multi-cloud GenAI platforms (Azure OpenAI + GCP Vertex AI + AWS Bedrock) with unified MLOps.
• Implement enterprise security : VPC peering, private model endpoints, and data residency compliance.
• Innovation & Strategy
• Pioneer GenAI use cases : Agentic workflows, AI-driven synthetic data generation, real-time fine-tuning.
• Establish AI governance frameworks : Model cards, drift monitoring, and red-teaming protocols.
• Cross-Functional Impact
• Partner with leadership to define AI roadmaps and ROI metrics (e.g., $ saved via AI-driven automation).
• Mentor junior engineers and evangelize GenAI best practices across the organization.

Qualifications

Must-Have Experience

Preferred Qualifications Additions

Skills Required

Pytorch, MLops, Python