Key Responsibilities

• ML Solution Architecture: Design and develop scalable AI/ML architectures with a focus on Deep Learning, Large Language Models (LLMs), and Natural Language Processing (NLP).

• Model Optimization: Enhance model efficiency, reduce latency, and optimize memory usage for real-time document processing.

• ML Infrastructure Development: Build and manage MLOps pipelines for experimentation, A/B testing, and deployment.

• LLM Pipeline Development: Develop and optimize pipelines using LangChain, LlamaIndex, and other AI frameworks.

• AI Strategy & Solutioning: Collaborate with cross-functional teams to align AI models with business objectives.

• Automation & Scalability: Create scalable and automated AI workflows for intelligent document processing.

• Research & Innovation: Stay updated on the latest AI advancements and integrate cutting-edge ML techniques into the platform.

Required Qualifications

• Experience: 8+ years in AI/ML within a software or product company.

• Expertise: Strong background in Deep Learning, Large Language Models (LLMs), and NLP (e.g., BERT, GPT, RoBERTa).

• Programming: Proficiency in Python with hands-on experience in ML frameworks like PyTorch, TensorFlow, LangChain, and SpaCy.

• LLM Experience: Practical experience with LLaMA, Zephyr, Mistral, and OpenAI APIs.

• MLOps & Deployment: Expertise in MLOps, cloud deployment, and AI model optimization.

• Problem-Solving: Strong analytical skills and a product-first mindset.