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 deployments

Requirements :

- 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