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).
Job Description:
Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences.
Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals.
Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning.
Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP, ensuring measurable outcomes.
Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges.
Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements.
Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact.
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.
