Ml/ai Technical Specialist Apac

Business Area: Sales Engineering Seniority Level: Mid-Senior level Job Description: At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises. We are currently seeking a customer-facing, hands-on AI and Machine learning expert with a track record of success to join us in Singapore. As an AI/ML Solution Lead for APAC you will: - Provide in-depth machine learning expertise to support the technical relationship with Cloudera’s customers, including product and solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption.- Support new customer opportunities from Proof of Concept (PoC) for Machine learning workloads especially Generative AI use cases using Open Source Models, Cloudera Applied Machine Learning prototypes and other cloud native integrations- Provide customers with Generative AI expertise and advisory through architecture designs, production reviews, and pre-sales support- Expand and grow Generative AI adoption for existing customer base especially for local APAC specific language and use cases- Lead and provide guidance in technical escalations to unblock AI customers in collaboration with Cloudera stakeholders- Provide expert perspective to key stakeholders to increase platform adoption through customer insights & feedback on a regular basis- Drive product improvement and influence roadmap with Engineering through deep technical insights especially taking the requirements from APAC countries where localized and privately hosted Generative AI solutions are preferred- Increase AI technical intensity in the field through upskilling, sharing best practices, and scaling repeatable IP- Travel to customer sites, conferences, and other related events as required.- Achievements are aligned to a team goal with annual sales targets, as well as to your participation in knowledge exchange with peers and the wider community We’ll be excited about you if you have: - Experience in building and deploying data and Machine Learning pipelines with a focus on automation.- Experience with building machine learning solutions, Machine Learning Operation frameworks like kubeflow, and leveraging specific machine learning architectures (e.g. deep learning, LSTM, convolutional networks, etc).- Experience in understanding a complex customer’s existing software workloads and the ability to define a technical migration roadmap to the Cloud reflecting specific customer needs.- Familiarity with machine learning programming frameworks such as LangChain, PyTorch, HuggingFace, and Tensorflow.- Familiarity with prompt tuning and delivering successful prototypes.- "Hands on" experience creating AI Proof of Concepts, and Minimum Viable Products (MVPs) leading to production deployments- Experience in architecting deployments for production in an enterprise setting including infrastructure knowledge, security, networking, and other considerations.- Design & Architecture: Architect, design, and implement robust, scalable, and secure agentic AI systems and frameworks. This includes defining agent logic, memory systems, tool integration, and orchestration mechanisms.- Agent Development: Develop and fine-tune AI agents capable of perceiving environments, reasoning about goals, formulating multi-step plans, and executing actions autonomously or with mínimal human oversight.- LLM Integration & Prompt Engineering: Leverage and integrate Large Language Models (LLMs) for agentic reasoning, communication, and planning. Conduct advanced prompt engineering, fine-tuning, and grounding techniques (e.g., Retrieval-Augmented Generation - RAG) to enhance agent performance and reliability.- Tool Integration: Design and implement interfaces for AI agents to interact with external tools, APIs, databases, and other software systems to perform specific actions and gather information.- Optimization & Evaluation: Optimize agent behavior and performance through iterative development, feedback loops, reinforcement learning, and robust evaluation methodologies. Implement continuous monitoring to track agent effectiveness and identify areas for improvement. You may also have: - Bachelor's degree or equivalent practical experience.- 5 years of experience in virtualization or cloud native architectures in a customer-facing or support role.Familiarity or direct exposure to key AI scenarios that are driving innovation in industries such as Financial Services, Retail, Healthcare, etc.- Technical Machine Learning Certification in Cloud (e.g., Azure, Amazon Web Services, Google certifications)- Presentation skills with a high degree of comfort with both large and small audience