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About the role
Role & responsibilities Design and implement machine learning solutions using a mix of classical ML models and LLM-based approaches. Select appropriate techniques for each problem, balancing accuracy, performance, cost, and operational complexity. Build and train models for tasks such as classification, similarity matching, extraction, normalization, and ranking. Develop LLM workflows including embeddings, prompt design, and retrieval-augmented generation where applicable. Preferred candidate profile Lead and mentor a team of backend and frontend developers, fostering a high-performing, team-oriented engineering culture. Own the technical direction, architecture, and strategy for LLM, AI Agent, and ML initiatives. Architect and build AI Agents, RAG pipelines (including multimodal RAG), LLM-based services, and evaluation frameworks. Design, build, and deploy scalable AI/ML systems from concept to production. Collaborate closely with PMs, ML Engineers, and Data Scientists to convert business requirements into AI-driven solutions. Oversee full SDLC for your squadensuring solid engineering practices around coding, testing, quality, and reliability. Conduct detailed technical reviews and provide guidance to maintain code quality. Troubleshoot performance, scalability, and reliability issues in production AI systems. Champion continuous improvement, automation, and innovation within the team. Keep the team up-to-date with advances in LLMs, LLMOps, fine-tuning techniques, vector search, and generative AI. Role & responsibilities Design and implement machine learning solutions using a mix of classical ML models and LLM-based approaches. Select appropriate techniques for each problem, balancing accuracy, performance, cost, and operational complexity. Build and train models for tasks such as classification, similarity matching, extraction, normalization, and ranking. Develop LLM workflows including embeddings, prompt design, and retrieval-augmented generation where applicable. Preferred candidate profile Lead and mentor a team of backend and frontend developers, fostering a high-performing, team-oriented engineering culture. Own the technical direction, architecture, and strategy for LLM, AI Agent, and ML initiatives. Architect and build AI Agents, RAG pipelines (including multimodal RAG), LLM-based services, and evaluation frameworks. Design, build, and deploy scalable AI/ML systems from concept to production. Collaborate closely with PMs, ML Engineers, and Data Scientists to convert business requirements into AI-driven solutions. Oversee full SDLC for your squadensuring solid engineering practices around coding, testing, quality, and reliability. Conduct detailed technical reviews and provide guidance to maintain code quality. Troubleshoot performance, scalability, and reliability issues in production AI systems. Champion continuous improvement, automation, and innovation within the team. Keep the team up-to-date with advances in LLMs, LLMOps, fine-tuning techniques, vector search, and generative AI.
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