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В Company hidden предлагают чётко очерченную ML-роль уровня Principal с актуальными задачами в рекомендациях, но без зарплатного диапазона и с обязательной работой в офисе в Лондоне оценить условия сложнее.
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Зарплата не указанаАктуальный стекЧёткая рольСильная AI-тема
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Principal Machine Learning Engineer, Matching & Recommendations (AI/Machine Learning): Building production recommendation, matching, ranking and personalisation systems for Bumble with an accent on retrieval, experimentation, two-sided marketplace optimisation and responsible AI. Focus on designing scalable ML pipelines, deploying AI agents with LLMs and MCP integrations, and balancing offline model performance with meaningful online member outcomes.
Location: London, UK; on-site
Company
hirify.global develops dating, friendship and relationship products including hirify.global Date, BFF and Badoo, focused on healthy and equitable connections.
What you will do
Define the technical strategy for AI and Machine Learning systems powering recommendations, matching, ranking and personalisation.
Design, develop and deploy production-grade models and end-to-end ML pipelines for high-traffic environments.
Build production AI agents using foundation models, fine-tuned LLMs, sub-agents, tools and MCP integrations.
Develop experimentation strategies using A/B testing, offline evaluation and online measurement.
Partner with Product, Engineering, Data Science and Analytics to solve ambiguous member and product problems.
Mentor senior individual contributors and promote responsible AI practices covering fairness, transparency, privacy and member safety.
Requirements
10–15 years of relevant experience or equivalent demonstrated scope, skills and impact.
Deep hands-on experience designing, building and deploying large-scale ML systems in production.
Strong Python proficiency and experience with PyTorch or TensorFlow.
Expertise in recommendation systems, ranking, retrieval, personalisation or NLP, including model architecture, features, loss functions and evaluation.
Experience prompting and fine-tuning LLMs, building AI agents, and creating scalable data and ML pipelines with Spark, Airflow or comparable technologies.
Ability to set technical direction, influence across teams, navigate ambiguity and mentor other engineers.
Culture & Benefits
Values include Kind Connections, Respect, Excellence, Curiosity and continuous learning.
Inclusive workplace with reasonable adjustments available throughout the hiring process.
AI may support parts of recruitment, but hiring decisions are made by people; participation in AI-supported interviews is voluntary.
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