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Senior Machine Learning Engineer, Applied AI Quality
Remote 10409 Engineering - Applied AI role with clear candidate location fit.
PostedRecently added
Eligible countries1 accepted country
Seniority signalSenior
Work settingRemote
Accepted candidate locations
USA
Role overview
Senior Machine Learning Engineer, Applied AI Quality
Requirements and responsibilities
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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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