Job Responsibilities :
- Train, fine-tune, and deploy machine learning models, including large language models (LLMs) to solve complex business problems.
- Develop and optimize Generative AI models, including diffusion models, LoRA, and advanced training techniques.
AI Workflows & Integration :
Design, implement, and optimize AI workflows leveraging LLMs, Generative AI, and third-party APIs.Build and deploy scalable AI pipelines to support real-time processing and large-scale data workflows.Transition AI prototypes into production-ready solutions in collaboration with cross-functional teams.ML Infrastructure and Performance Optimization :
Scale data pipelines, optimize training and inference systems, and ensure reliability across all ML systems.Enhance system performance, scalability, and reliability to meet evolving customer and business needs.Monitor and improve deployed solutions based on feedback and performance metrics.Backend Engineering and Cloud Deployment :
Develop backend features and automation tasks to integrate AI systems seamlessly into Karbon's platform.Leverage cloud platforms (AWS, GCP, Azure) to design scalable GPU systems for AI / ML deploymentsRequirements :
4+ Years of experience on AI project development.Strong understanding of fundamental ML algorithms, including transformer-based architectures.Proven experience working with and fine-tuning large language models (LLMs) like GPT, BERT, or similar frameworks.Hands-on experience deploying and optimizing Generative AI models with advanced knowledge of diffusion models, LoRA, and similar techniques.Strong proficiency in Python, Node.js with experience in frameworks like Express, TensorFlow and PyTorch.Cloud & Infrastructure : Proven expertise in cloud environments (AWS, GCP, Azure).Proficiency in building and integrating APIs and end-to-end AI workflows.Should be able to mentor team pf 3-5 Developers or Work on POCs as IC(ref : hirist.tech)