Data Science Lead

7 days ago

Bengaluru Delhi NCR Pune, India Bean Hr Consulting Full time ₹ 1,04,000 - ₹ 1,30,878 per year

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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