Job Description
📋 Description Design and oversee end-to-end ML architecture, from data ingestion to model serving and monitoring. Define long-term roadmap for AI infrastructure and orchestration. Oversee the AI/ML ecosystem design, implementation, and maintenance. Set the standard for MLOps to ensure ML ecosystem is testable and scalable. Lead cross-functional collaboration with product, data scientists and ML engineers. Mentor engineers through high-level design reviews and performance optimization. 🎯 Requirements Bachelor’s or Master’s in CS/Math or equivalent deep professional experience. 7+ years software engineering with 4+ years deploying ML models in production. Proven Staff/Senior-level leadership with architecture ownership and mentoring. Deep expertise in MLOps, model training, deployment, monitoring, and lifecycle. Strong cloud experience (AWS, Azure, or GCP) for scalable AI workloads. Python proficiency and ML frameworks (TensorFlow, PyTorch, scikit-learn). 🎁 Benefits Flexible hybrid work model with in-person collaboration when needed. Strong commitment to diversity, equity, inclusion, and belonging. Opportunity to work on tech that helps people do good in the world. Growth opportunities and meaningful, purposeful work. Accommodations for disabilities available upon request. Cloud certifications are a nice-to-have.
