AI Engineer

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify.

• Act as the primary technical counterpart to CTOs, VPs of Engineering, and research/engineering leadership.
• Lead executive conversations using a structured, answer-first (BLUF) approach.
• Manage escalations and expectations with composure and integrity.
• Build long-term trusted relationships by recommending evidence-based solutions.
• Ask excellent questions to uncover the client's real need - the "question behind the question." Understand their model, which metrics they want to move, and how they intend to train or evaluate it.
• Draw on a solid understanding of how LLMs are trained and fine-tuned to have credible conversations with their technical leaders, understand their data strategy, and proactively propose the data that will solve their problem - with options and rationale.
• Design and build the data solutions yourself: configure data-labeling components and quality controls, develop user interfaces and AI-driven solutions (e.g. agentic systems, RAG, synthetic data generation), and integrate them into automated, multi-stage pipelines that produce data for AI training and evaluation.
• Architect and reason about complex, multi-stage solutions end to end; run experiments to prove the pipeline delivers data of the required quality and speed; iterate from MVP toward production.
• Provide technical leadership across multiple client engagements, establish reusable engineering standards and best practices, and mentor Solution Engineers and Technical Consultants to raise the overall technical bar of the organization.
• Own delivery end to end - timelines, quality, and scalability - and the commercial outcome: Gross Margin and Contribution Margin, with the levers, trade-offs, and next checkpoints named, not just described.
• Identify and drive expansion opportunities.

• Executive communication: You can confidently lead conversations with CTOs, VPs, and senior technical stakeholders - clear, concise, structured, persuasive, and calm under pressure. Professional English (C1+) is essential.
• Strong understanding of modern LLM development: You understand how modern LLMs are trained, fine-tuned, and evaluated (including SFT, RLHF/RLAIF, DPO/PPO, reward modeling, and LoRA/PEFT). You're comfortable discussing these topics with senior technical stakeholders and translating their goals into effective AI data solutions.
• Hands-on solution engineering: You've designed complex AI solutions, built multi-stage pipelines, and developed AI-driven systems (e.g. agentic workflows, RAG, or synthetic data generation). You're comfortable working in Python (NumPy, Pandas), integrating APIs, and independently prototyping LLM-powered solutions.
• Solid software engineering foundations: You understand version control, testing, MVP thinking, and iterative development.