Principal Machine Learning Architect

at  Egen Solutions

Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results.
We are looking for a Principal Machine Learning Engineer who will play a critical role in our Data Science team; focusing on the development and enhancement of our Machine Learning Operations (MLOps) platform. This role demands a unique blend of cloud architecture expertise, AI/ML knowledge, and leadership skills to lead a team in building and maintaining a robust, efficient, and cutting-edge MLOps platform.

• 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.