Resumo da vaga

Senior Machine Learning Engineer, Applied AI Quality

Requisitos e responsabilidades

Conteúdo da vaga extraído em seções para revisão mais rápida.

You Will

  • Lead the technical strategy and architecture for AI-driven quality and evaluation systems used across products and teams.
  • Drive the development of scalable systems that use LLMs, agents, and behavioral signals to evaluate quality, detect regressions, and generate product insights.
  • Define long-term approaches for evaluation, measurement, and quality intelligence across complex product surfaces.
  • Translate ambiguous organizational needs into clear technical direction, roadmap priorities, and platform capabilities.
  • Influence engineering standards and best practices for building reliable, measurable, and trustworthy AI systems.
  • Lead complex cross-functional initiatives spanning product, infrastructure, data, and applied AI teams.
  • Mentor and level up engineers across the organization through technical leadership, design reviews, and systems thinking.
  • Identify leverage opportunities where AI systems can fundamentally improve how teams understand, debug, and improve product behavior.

You Have

  • 5+ years of experience in software engineering, machine learning engineering or applied AI.
  • Deep experience designing and shipping large-scale AI/ML systems in production environments.
  • Strong expertise with LLMs, agents, evaluation systems, retrieval architectures, and modern AI infrastructure.
  • Proven ability to lead ambiguous, high-impact technical initiatives from concept through adoption across multiple teams.
  • Strong systems thinking and architectural judgment, with the ability to balance experimentation, scalability, and operational rigor.
  • Experience defining technical strategy and influencing roadmaps beyond your immediate team.
  • Excellent communication and cross-functional leadership skills, with the ability to align engineering, product, and organizational priorities.
  • A track record of creating leverage through platforms, frameworks, and systems that enable other engineers and teams to move faster and make better decisions.
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