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Toloka AI supports frontier model post-training by building domain-specific reinforcement learning environments, tasks, and evaluation frameworks designed by real practitioners. Mindrift, powered by Toloka - a leading enterprise AI and machine learning data partner since 2014 - connects top domain experts with cutting-edge AI initiatives. Backed by Toloka's deep expertise in scalable data generation, crowd technology, and applied ML systems, Mindrift enables experts to shape how next-generation generative models learn, reason, and perform. We are launching a Management Consulting domain focused on translating real-world consulting engagements into structured learning environments for advanced AI systems. To do this credibly, we are assembling a team of strategy consultants from top-tier firms who can convert authentic project experience into end-to-end examples - from problem structuring and work planning to analysis, synthesis, and client-ready recommendations. You will join a growing team of consultants from leading strategy firms shaping how AI learns high-level business reasoning. Important: This role is exclusively for consultants with direct experience at a top-tier strategy consulting firm. If you do not have hands-on project experience at one of the firms listed below, please do not apply. This requirement ensures the domain is built by practitioners trained to the highest standards of structured problem-solving and client delivery. Eligible firms: McKinsey & Company, Boston Consulting Group (BCG), Bain & Company, Oliver Wyman, Roland Berger, Monitor Deloitte (Deloitte S&C), EY-Parthenon, Kearney, and Strategy& (PwC).
What You'll DoBuild realistic consulting project environments - create detailed project scenarios grounded in real engagement dynamics: industry context, financials, constraints, conflicting inputs, and incomplete information. Design structured consulting tasks for AI agents - break projects into discrete tasks that mirror real consulting work: market sizing, commercial due diligence, cost optimization, growth strategy, operational diagnosis, benchmarking, and more. Define evaluation criteria and quality standards - develop grading frameworks, evaluation rubrics, and golden-answer solutions for each task, used to train and calibrate an LLM-based grading system that evaluates AI outputs at scale. This is a remote, project-based, individual-contributor role focused on analytical design and evaluation.
Qualifications / RequirementsSkills & Requirements: 3+ years at McKinsey, BCG, Bain, Oliver Wyman, Roland Berger, Monitor Deloitte, EY-Parthenon, Kearney, or Strategy&. Strong structured problem-solving and hypothesis-driven thinking. Ability to translate vague problems into clear analytical steps and deliverables. High attention to logical consistency and output quality. Independent, self-directed working style. Clear written English (B2+).
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