Location : Remote - LATAM Schedule : Full-time (8 hrs / day) — must have 4 hrs overlap with PST?
About the Role: We'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.
Lead 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.
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