Data Scientist - Generative AI

Job Details :

As a Data Scientist specializing in Generative AI, you will :

- Shape Next-Generation Solutions: Partner with cross-functional teams to design and implement AI-driven systems that transform user experiences and streamline business processes.

- Enhance AI Through Data: Employ data-centric methodologies to improve model accuracy and responsiveness by curating high-quality datasets and optimizing real-time performance.

- Finetune Industry-Specific Gen AI Models: Adapt and fine-tune large language models for domain-specific applications using advanced techniques like instruction tuning, domain adaptation, and reinforcement learning from human feedback (RLHF).

- Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions.

- Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation.

- Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency.

Key Responsibilities :

- Design AI Systems: Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization.

- Develop NLP Pipelines: Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation.

- Integrate Multi-Modal Systems: Combine data modalities such as text, images, and metadata for enriched user interactions and insights.

- Optimize AI Pipelines: Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production.

- Collaborate on AI Innovation: Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions.

Experience :

- BS/MS in Computer Science, Math, Physics, Engineering, Statistics, or another quantitative or computational field. Advanced degrees preferred.

- Fine tuning experience of Large Language models (LLMs, VLLMs, or Vision model)

- Distributed training or inference experience with frameworks like Ray, vllm, openllm, bentoML etc.

- Experience with frameworks like like LangChain, Llamaindex for building maintainable, scalable Generative AI applications.

- Deployment experience or optimized hosting experience of Large Language models (LLMs, VLLMs, or Vision model)

- Experience working with any Vector database like Milvus, FAISS, ChromaDB etc

- Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc

- Experience with prompt engineering

- Keeping up with latest market trends

- Experience working with open source large language models from HuggingFace

- Experience working with atleast one public cloud provider such as Azure, AWS or GCP

- Experience working with container technology like Docker, ECS etc

- Experience with DevOps practices and CI/CD pipelines for data solutions

- Experience in deploying solutions to production with Kubernetes or OpenShift

- Experience with managing ML workflows with MLFlow or KubeFlow