Principal Machine Learning Architect

Responsibilities:

• Architectural Leadership: Lead the architecture and design of our MLOps platform, with a focus on GCP Vertex AI and Kubeflow related platforms. 
•  Responsible AI Solutions: Develop solutions focused on Responsible AI, including explainability, data drift detection, and fairness metrics. Ensure adherence to ethical AI practices. -
• Developer Experience: Drive enhancements to the MLOps platform to optimize developer experiences for data and ML engineers, incorporating streamlined workflows and advanced tools. -
• Collaboration with AI/ML Experts: Collaborate with AI/ML experts across domains such as Computer Vision, NLP, Forecasting, LLMs, and synthetic data. Integrate the latest advancements into the MLOps platform. -
• AI/ML Reliability and Observability: Work closely with the AI/ML Reliability engineering team to develop components that ensure the reliability and observability of our platform. -
• Experience in Platform Development: Candidates should have prior experience working with platform teams, especially in the data and AI/ML space. -
• Cloud Platform Expertise: Proficiency in cloud platforms is essential. Experience in expanding platforms to on-premises and edge deployments is a plus. -
• Cross-functional Collaboration: Ability to work closely with peer cloud teams, data scientists, and product managers to align platform development with organizational objectives.   

What we're looking for:

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, (or a related field is preferred)
• 10+ years of experience in the technology or data field
• Proficient engineering and coding skills in Python and other languages.
• Strong background in AI/ML or Data Sciences technologies and platform development.
• Great multi-disciplinary knowledge of technology space (data, cloud, UI, security)
• Excellent communication, leadership, and project management skills.