Senior Software Engineer - AI

ML Modeling and Deployment

• 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 Karbons platform.
• Leverage cloud platforms (AWS, GCP, Azure) to design scalable GPU systems for AI/ML deployments.

Job Requirement

• 4+ Years of experience on AI project developemnt
• 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