Top Tech Jobs & Startup Jobs

Own the launch and growth of Toloka’s real-business data partnership function. Source partners through outbound prospecting, pitch data licensing opportunities, negotiate and close pilots and ongoing collection agreements, and coordinate execution with legal, finance, sales, delivery, and partnerships teams. Build repeatable sourcing and partner-management processes while managing deals with businesses, data providers, and aggregators across global markets.

Design and deliver end-to-end data labeling and ML pipelines using Toloka's platform. Act as primary technical contact for clients, lead discovery and solution design, run pilots, monitor KPIs, troubleshoot delivery, and optimize quality, cost, and scalability while coordinating internal teams and stakeholders.

Serve as a senior client-facing technical lead who designs and builds data-generation, labeling, and evaluation pipelines for LLMs. Partner with executive stakeholders to diagnose needs, propose data strategies, architect multi-stage automated pipelines (including RAG, synthetic data, agentic systems), deliver solutions end-to-end, and own commercial outcomes and expansion opportunities.

Serve as the senior client-facing technical lead to design and build data-generation, labeling, and evaluation pipelines for LLMs. Partner with executive stakeholders, diagnose data needs, architect multi-stage automated solutions (RAG, agentic workflows, synthetic data), run experiments, deliver production-ready pipelines, mentor engineers, and own delivery timelines and commercial outcomes.

Design and deliver end-to-end data labeling and ML pipelines on Toloka's platform. Serve as primary technical contact, run pilots, configure workflows and quality controls, monitor KPIs, troubleshoot delivery, and advise customers on data, evaluation, and model-training best practices.

Design and deliver end-to-end data labeling and ML data pipelines using Toloka's platform. Act as primary technical contact for customers, lead discovery and solution design, configure tooling (including agentic systems and RAGs), run pilots, monitor KPIs, troubleshoot delivery, and optimize for quality, cost, and scalability while coordinating cross-functional teams.

Design, train, fine-tune, distill, and deploy LLM-based and agentic ML models. Build and operate agent workflows in Python, run evaluation and benchmarking, select models and cost strategies, and manage production monitoring and observability for model performance and reliability.