Job
Description
As an AI Architect at our company, your role will be crucial in defining and implementing the architecture for deploying machine learning models, including Generative AI and LLM solutions, into production. You will lead a talented team of Data Scientists, Backend Developers, and DevOps Engineers, fostering innovation, technical excellence, and operational efficiency. Key responsibilities: - **Architectural Leadership:** - Design, develop, and own the scalable, secure, and reliable end-to-end architecture for deploying and serving ML models with a focus on real-time inference and high availability. - Lead the strategy and implementation of the in-house API wrapper infrastructure for exposing ML models internally and externally. - Define architectural patterns, best practices, and governance for MLOps, ensuring robust CI/CD pipelines, model versioning, monitoring, and automated retraining. - Evaluate and select the optimal technology stack for our ML serving infrastructure, balancing performance, cost, and maintainability. - **Team Leadership & Mentorship:** - Lead, mentor, and inspire a diverse team of Data Scientists, Backend Developers, and DevOps Engineers through architectural decisions and technical challenges. - Foster a collaborative environment that encourages knowledge sharing, continuous learning, and innovation. - Drive technical excellence, code quality, and adherence to engineering best practices. - **Generative AI & LLM Expertise:** - Architect and implement solutions for deploying Large Language Models (LLMs), including strategies for efficient inference and context management. - Drive the adoption and integration of techniques like Retrieval Augmented Generation (RAG) to enhance LLM capabilities. - Develop strategies for fine-tuning LLMs for specific tasks and domain adaptation. - Stay updated on advancements in Generative AI and evaluate their applicability to our business needs. - **Collaboration & Cross-Functional Impact:** - Collaborate with Data Scientists to optimize models for production and integrate them into the serving infrastructure. - Partner with Backend Developers to build secure, performant APIs for ML predictions. - Work with DevOps Engineers to automate deployment, monitoring, and scaling of the AI infrastructure. **Qualifications Required:** - Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or related field. - Experience: 10+ years in software engineering, with 5+ years in an Architect or Lead role. - Technical Skills: Proficiency in MLOps principles, Python, web frameworks, containerization, cloud platforms, LLMs, RAG systems, distributed systems, and monitoring tools. - Leadership & Soft Skills: Strong leadership, analytical, communication, and problem-solving skills. If you are proactive, self-driven, and have a continuous learning mindset, and possess the bonus points mentioned, you are the ideal candidate for this role. Join us in our journey of innovation and technical excellence in AI architecture. As an AI Architect at our company, your role will be crucial in defining and implementing the architecture for deploying machine learning models, including Generative AI and LLM solutions, into production. You will lead a talented team of Data Scientists, Backend Developers, and DevOps Engineers, fostering innovation, technical excellence, and operational efficiency. Key responsibilities: - **Architectural Leadership:** - Design, develop, and own the scalable, secure, and reliable end-to-end architecture for deploying and serving ML models with a focus on real-time inference and high availability. - Lead the strategy and implementation of the in-house API wrapper infrastructure for exposing ML models internally and externally. - Define architectural patterns, best practices, and governance for MLOps, ensuring robust CI/CD pipelines, model versioning, monitoring, and automated retraining. - Evaluate and select the optimal technology stack for our ML serving infrastructure, balancing performance, cost, and maintainability. - **Team Leadership & Mentorship:** - Lead, mentor, and inspire a diverse team of Data Scientists, Backend Developers, and DevOps Engineers through architectural decisions and technical challenges. - Foster a collaborative environment that encourages knowledge sharing, continuous learning, and innovation. - Drive technical excellence, code quality, and adherence to engineering best practices. - **Generative AI & LLM Expertise:** - Architect and implement solutions for deploying Large Language Models (LLMs), including strategies for efficient inference and context management. - Drive the adoption and integration of techniques like Retrieval Augmented Generation (RAG) to enhance LLM capabilities. - Develop strategies for fine-tuning LLMs for specific tasks and domain adaptation. - Stay updated on advancements in Generative AI and evaluate their applicabil
