Location: Remote - LATAM Schedule: Full-time (8 hrs/day) — must have 4 hrs overlap with PST✨ About the RoleWe’re looking for a hands-on Machine Learning Engineering Manager to lead cross-functional teams in designing, training, and deploying large-scale ML and LLM systems.You’ll drive the full lifecycle of AI development — from research and experimentation to distributed training and production deployment — while mentoring top-tier engineers and partnering closely with product, research, and infra leaders.This role blends deep ML/MLOps expertise with strong leadership and execution, ensuring all AI initiatives translate into measurable business impact. Key ResponsibilitiesLead and mentor ML engineers, data scientists, and MLOps professionals.Manage end-to-end ML/LLM project lifecycle: data pipelines, training, evaluation, deployment, and monitoring.Provide technical direction for distributed training, large-scale model optimization, and system architecture.Collaborate with Research, Product, and Infrastructure teams to define objectives, milestones, and KPIs.Implement MLOps best practices: experiment tracking, CI/CD, model governance, observability.Manage compute resources, cloud budgets, and enforce Responsible AI + data security standards.Communicate technical progress, blockers, and results clearly to leadership and stakeholders.