
Data Science Lead
7 days ago
Job Title: Lead - Data Science
Gurgaon / Noida/Pune/Bengaluru
7-10 Years Experience
About the Role
We are looking for an experienced Senior Generative AI Developer to lead the design, development, and deployment of large-scale enterprise-grade GenAI systems. This is a hybrid role requiring both deep hands-on expertise and strategic leadership, working across multi-cloud environments and managing the full lifecycle of AI/ML systems.
Key Responsibilities
Technical Leadership
- Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for performance-cost optimization.
- Design and scale training pipelines using FSDP, DeepSpeed on GPU/TPU clusters.
Cloud-Native AI Development
- Build and manage multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps.
- Implement enterprise-grade security: VPC peering, private endpoints, and regulatory compliance (e.g., data residency).
Innovation & Strategy
- Drive pioneering initiatives such as Agentic workflows, real-time fine-tuning, and synthetic data generation.
- Define and execute AI governance: model cards, drift monitoring, red-teaming protocols.
Cross-Functional Impact
- Collaborate with product and business teams to define GenAI strategy and ROI metrics (e.g., automation cost savings).
- Mentor junior engineers and promote GenAI best practices across the organization.
Required Qualifications
- Education: Bachelors/Masters in CS, AI/ML, or equivalent experience.
- Experience: 5+ years in ML, 2+ years specifically in Generative AI.
Technical Mastery
- Languages: Expert in Python
- Frameworks: PyTorch, TensorFlow Extended (TFX), ONNX Runtime
- Certifications: Azure AI Engineer Expert, GCP ML Engineer (preferred)
GenAI Expertise
- Experience shipping production-scale GenAI systems (e.g., 10k+ QPS chatbots, GitHub Copilot-scale models).
- Mastery of advanced LLM techniques (LLM orchestration, guardrails, self-reflective prompting).
Must-Have Experience
- Azure: Azure OpenAI, MLOps Pipelines, Cognitive Search
- GCP: Vertex AI Evaluation, Gemini Multimodal, TPU v5 Pods
- Built RAG systems using hybrid search (vector + keyword) and real-time data hydration
- Led AI compliance in regulated domains (finance, healthcare)
Preferred Additions
- Experience with multi-cloud GenAI deployments (e.g., training on GCP, serving on Azure).
- Certification in Azure and/or GCP AI tracks.
- Exposure to autonomous agents, vector databases, and AI-driven business automation.
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