Note: The job is a remote job and is open to candidates in USA. Toloka AI is hiring a Forward Deployed AI Engineer to partner with client technical leaders and solve complex AI data challenges. The role designs and delivers data-generation, labeling, and evaluation solutions and pipelines, while providing technical leadership across engagements and owning delivery and commercial outcomes.
Responsibilities
- 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 ("based on your goal, you likely need this, or this")
- 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
Skills
- 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
- 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
- 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
- You understand version control, testing, MVP thinking, and iterative development
- You enjoy working through ambiguity, asking the right questions, and translating business or research goals into clear AI data and evaluation strategies
- 8+ years delivering complex AI, ML, or data projects end to end, with experience influencing technical direction beyond individual projects
- You take responsibility for outcomes, make thoughtful trade-offs between time, cost, and quality, and are comfortable owning both technical and commercial success
- Experience building production software is a strong plus
- Experience establishing engineering standards, mentoring engineers, or leading cross-functional technical initiatives is highly valued
- Experience in top-tier strategy consulting (McKinsey, Bain, BCG) and/or as an applied ML / LLM engineer is a strong advantage
- Hands-on experience training or fine-tuning LLMs and/or building agentic systems (helps you reason about client needs - though the role itself is about building data solutions, not training models)
- Advanced degree (MSc/PhD) in AI, CS, or a related field
- Experience in crowdsourcing and/or data-centric AI, and with fast-paced, multi-project delivery for frontier AI clients
Benefits
- Freelance (B2B) collaboration, with a path into a project team if things go well
- Flexible, fully remote schedule (40 hours per week)
- Work at the leading edge of AI development, alongside a dedicated and dynamic team of experts
- Projects with customers that are AI industry leaders and well-known household names
- Friendly community
Company Overview