Artificial Intelligence / Machine Learning Lead

As an AI/ML Lead at the company, your role will involve designing, developing, and deploying AI-driven lending automation solutions, focusing on NLP workflows, GenAI orchestration, and valuation process automation. This position requires a balance of coding and delivery responsibilities with architecture and leadership tasks. You will collaborate with various teams to seamlessly integrate AI capabilities into the enterprise platform. **Key Responsibilities:** - Architect and implement end-to-end AI/ML features aligned with lending workflows, including NLP Document Parsing OCR, Valuation Automation, and GenAI Orchestration. - Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures. - Select, train, fine-tune, and deploy models, and implement model monitoring pipelines for accuracy and retraining triggers. - Collaborate with Data Engineering for AI-ready data pipelines, data labeling, augmentation, and versioning processes. - Design and implement multi-step AI orchestration layers, build custom prompt chains, and tools for complex workflows. - Translate complex AI concepts into clear business benefits, mentor developers, and track AI feature KPIs. **Qualifications Required:** - Total Experience: 7 - 12 years in software engineering, with 3 years hands-on AI/ML solution delivery. - Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow). - Strong experience with NLP pipelines, AI orchestration frameworks, REST API design, and microservices. - Deep understanding of data structures, MLOps tools, cloud-native AI deployments, and communication skills for technical-to-business translation. The company is seeking a talented individual with a proven record of deploying AI/NLP features in production environments, along with expertise in various AI technologies and frameworks. If you have experience in Fintech or lending automation platforms, financial document workflows, and bonus skills like RAG pipelines and custom LLM training, it will be considered a plus. As an AI/ML Lead at the company, your role will involve designing, developing, and deploying AI-driven lending automation solutions, focusing on NLP workflows, GenAI orchestration, and valuation process automation. This position requires a balance of coding and delivery responsibilities with architecture and leadership tasks. You will collaborate with various teams to seamlessly integrate AI capabilities into the enterprise platform. **Key Responsibilities:** - Architect and implement end-to-end AI/ML features aligned with lending workflows, including NLP Document Parsing OCR, Valuation Automation, and GenAI Orchestration. - Develop production-grade AI services in Python, integrating with REST/GraphQL APIs, microservices, and event-driven architectures. - Select, train, fine-tune, and deploy models, and implement model monitoring pipelines for accuracy and retraining triggers. - Collaborate with Data Engineering for AI-ready data pipelines, data labeling, augmentation, and versioning processes. - Design and implement multi-step AI orchestration layers, build custom prompt chains, and tools for complex workflows. - Translate complex AI concepts into clear business benefits, mentor developers, and track AI feature KPIs. **Qualifications Required:** - Total Experience: 7 - 12 years in software engineering, with 3 years hands-on AI/ML solution delivery. - Proficiency in Python (FastAPI, Flask, LangChain, Hugging Face Transformers, PyTorch/TensorFlow). - Strong experience with NLP pipelines, AI orchestration frameworks, REST API design, and microservices. - Deep understanding of data structures, MLOps tools, cloud-native AI deployments, and communication skills for technical-to-business translation. The company is seeking a talented individual with a proven record of deploying AI/NLP features in production environments, along with expertise in various AI technologies and frameworks. If you have experience in Fintech or lending automation platforms, financial document workflows, and bonus skills like RAG pipelines and custom LLM training, it will be considered a plus.