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Perplexity AI is hiring an experienced Machine Learning Engineer to drive search quality improvements across middle and late-stage ranking systems. This is a high-impact individual contributor role focused on owning ranking-quality problems end-to-end—from evaluation design and bottleneck identification through solution development and safe deployment.
Key responsibilities include:
- Advancing search quality through models, data, evaluation, infrastructure, and other high-leverage approaches
- Owning ranking-quality problems completely: defining evaluation metrics, identifying performance bottlenecks, building solutions, and shipping safely to production
- Training and evaluating retrieval, ranking, and classification models using neural and LLM-based approaches
- Building and operating ranking infrastructure including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring
- Making sound trade-offs across quality, latency, reliability, cost, and engineering complexity
- Collaborating across Data, AI, Infrastructure, and Product teams while retaining final quality ownership
Required qualifications:
- Deep understanding of search or recommender systems and their evaluation methodologies
- Proven track record owning a large-scale production ranking system or substantial class of quality problems
- Strong machine-learning and software-engineering skills spanning data pipelines, model development, serving infrastructure, and monitoring
- Ability to drive ambiguous, cross-functional problems independently without continuous task decomposition
- Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime optimization
- Minimum 5 years of relevant industry experience
This role is ideal for a senior engineer with deep expertise in production ML systems who thrives owning complex, end-to-end ranking challenges at scale.
About Perplexity AI
AI / Data / Infrastructure — AI answer engine and search product for consumers and enterprises.
