AI Technical Product Manager
3 settimane fa
As an AI, Technical Product Manager you will bridge the gap between technical and business perspectives to ensure that AI solutions deliver value, are ethically responsible, and align with the organization's overall strategy.
He/She is a professional responsible for designing and overseeing the development of AI systems and solutions within an organization. Their role is crucial in ensuring that AI projects align with the organization's goals, are technically sound, and deliver value.
Reports: VP of Artificial Intelligence
Responsibilities:- Work closely with the AI Leadership team to set the vision of the AI-centric product at different scales—short-term, mid-term, and long-term.
- Collaborate with the AI Product manager to understand business requirements and objectives. They then design AI solutions that can address these needs effectively. This involves selecting appropriate AI techniques, algorithms, and technologies.
- At a high level, evaluate and propose the solutions to implement, so that take technical feasibility into account to help craft the AI product strategy. This could involve assessing new and emerging technologies to identify promising ones.
- About the specifics of AI product requirements, he/she is about using tech knowledge to guide formulation and to help estimate realistic timelines for implementing product plans based on tech feasibility.
- Decide which Machine Learning or Deep Learning models are suitable for a given problem, considering model complexity, training data availability, and computational resources.
- Assess and plan the necessary computational infrastructure for AI projects, which may include GPUs, TPUs, cloud resources, and distributed computing setups.
- Design solutions that can scale as the data and computational demands grow. This involves considering distributed computing, containerization, and other scaling techniques.
- Oversee the integration of AI solutions into existing IT systems and workflows, ensuring that AI seamlessly fits into the organization's operations.
- Writing detailed documentation of AI system architectures, models, and processes is essential for transparency and future reference.
- Must stay up-to-date with the latest advancements, tools, and best practices.
- At least 5 years of experience in data mining, data analysis, and Machine Learning, working on large-scale projects and heterogeneous data sets.
- Strong analytical skills.
- Strong statistics, data mining, and machine learning foundations.
- Experience with Generative AI around topics such as LangChain, LLama Index, RAG, Hugging Face, Prompt Engineering, AI Agents.
- Strong teamwork attitude.
- Solid software engineering expertise.
- Fluency in English.
- Master's degree in Computer Science, Math, Statistics, Physics, or similar.
- Knowledge of service-oriented computing, specifically the REST paradigm, and microservices
- Hands-on experience with commercial cloud platforms, such as Amazon Web Services and Google Cloud
- Attitude to work and deliver within the context of agile development methodologies
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