Tech Rakers - Cupertino, CA
posted 10 days ago
Full-time
Cupertino, CA
Professional, Scientific, and Technical Services
About the position
The Technical Product Manager for the AIML Platform will oversee product management for a critical component of the Client Data, Analytics & AI initiative. This role focuses on building and expanding the AIML platform using modern, cloud-based technologies, ensuring it meets the needs of data scientists and developers while aligning with the latest FinTech advancements. The position involves collaboration with various teams to translate business requirements into a clear product vision and roadmap, driving the development of features and capabilities essential for AI model execution and validation.
Responsibilities
- Manage product development for the AIML Platform, ensuring it is feature-relevant, secure, and scalable.
- Collaborate with ML Engineering and Data Science teams to understand requirements and use cases.
- Drive the development of ML model validation environments using cloud capabilities like Azure ML Studio.
- Implement runtime execution capabilities for AIML models using Azure Kubernetes Services.
- Empower developers with self-service capabilities while ensuring data safety and onboarding efficiency.
- Build a GenAI Platform to facilitate LLM integration, development, and execution.
- Translate business needs into a clear product vision and roadmap, ensuring alignment with stakeholder requirements.
- Work closely with engineering teams on a sprint-by-sprint basis to prioritize and deliver key features.
Requirements
- Bachelor's degree or equivalent work experience.
- 3 to 5 years of product management experience.
- 5 to 7 years of engineering or technical experience outside of product management.
Nice-to-haves
- Experience in ML Engineering (highly preferred).
- Passion for the FinTech space or experience in the financial industry (optional).
- Good understanding of GenAI patterns including RAG.
- Familiarity with ML model development life cycle (E2E knowledge).
- Experience with cloud platforms (Azure, AWS, Google Cloud Platform).
- Knowledge of Docker, Containers, Kubernetes, and Terraform.
- Experience with Data Science and Machine Learning (optional but preferred).
- Proficiency in Python (highly preferred).
- Understanding of IAM, Security & networking on Cloud (highly preferred).
- Familiarity with Spark & Distributed systems (preferred).
- Experience with ML tools like Azure ML Studio, Azure OpenAI, Kubeflow, MLFlow (highly preferred).
- Familiarity with Kafka, DevOps, SRE, CI/CD, TLS/SSH, and IAC concepts.
