Описание:
Perplexity develops search software and focuses on improving search quality through ranking models, data, evaluation, and production infrastructure.
Задачи:
- Improve search quality across the middle and later stages of ranking through models, data, evaluation, infrastructure, and other available levers
- Own ranking-quality problems end to end by defining evaluations, identifying bottlenecks, building solutions, and shipping them safely
- Train and evaluate retrieval, ranking, and classification models, including neural and LLM-based approaches where appropriate
- Build and operate ranking infrastructure, including feature computation, low-latency inference, multi-stage cascades, deployment, and monitoring
- Make trade-offs across quality, latency, reliability, cost, and engineering complexity
- Collaborate across Data, AI, Infrastructure, and Product while retaining ownership of the final quality outcome
Требования:
- Deep understanding of search or recommender systems and their evaluation
- Proven ownership of a large-scale production ranking system or a substantial class of quality problems
- Strong machine-learning and software-engineering skills across data, models, serving, and monitoring
- Ability to drive ambiguous, cross-team problems without continuous task decomposition
- Exceptional depth in either modern neural ranking methods or low-latency ranking systems and runtime
- Minimum 5 years of relevant industry experience
Условия:
No conditions specified
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machine learning engineer in search ranking in London employer: Enfint
As a leading innovator in AI products for major publishers, our company offers an inspiring work environment where creativity and technology intersect. We prioritise employee growth through continuous learning opportunities and foster a collaborative culture that values diverse perspectives. Located in a vibrant city, we provide competitive salaries, relocation support, and the chance to make a real impact in the media landscape.
