About the position
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).
Responsibilities
• Build 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.
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+)