Senior Solution Engineer

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Toloka

51 - 200 employees

Founded 2014

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

Toloka is a company that specializes in enhancing AI development and fine-tuning of Large Language Models (LLMs). They provide expert data for supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) across multiple domains and languages. Trusted by leading machine learning and AI teams, Toloka offers a comprehensive platform for data labeling, AI evaluation, and AI safety. Their advanced technology platform supports diverse and scalable data collection with a global workforce, ensuring high-quality and reliable data for AI projects. Toloka is included in Gartner’s 2023 Hype Cycle for Generative AI and is compliant with various international standards, including GDPR and HIPAA.

📋 Description

• Ensure top-level delivery of our product, its correct configuration, and the deployment of tailored AI data solutions that meet our customers’ needs • Design and implement data labeling pipelines • Act as a trusted technical advisor for customers • Help customers understand their data needs, discover new opportunities, and build scalable AI solutions • Act as the primary technical point of contact for customers across technical and executive stakeholders • Lead discovery conversations to deeply understand client goals, problems and quality criteria • Translate client needs into clear, actionable solution designs and delivery plans • Advise customers on best practices in data collection, data quality, evaluation, and model training workflows • Set expectations proactively, communicate progress regularly, and manage risks and trade-offs transparently • Identify expansion opportunities and additional ways Toloka can create value through data and AI solutions • Design end-to-end data solutions using Toloka’s platform • Configure data labeling components and quality controls and develop user interfaces • Run experiments and pilots to validate quality, throughput, and cost assumptions • Lead technical execution during delivery, coordinating internal teams and external stakeholders as needed • Ensure solutions meet agreed quality, performance, and scalability requirements • Own delivery outcomes holistically - including technical performance, quality, timelines, and financial efficiency • Monitor key KPIs and act on deviations • Prioritize work based on customer impact and business value • Analyze data to identify failure modes, inefficiencies, and opportunities for improvement • Continuously optimize solutions through iteration, automation, and adoption of new technologies • Troubleshoot delivery, process, or technical issues in collaboration with support, infrastructure, and product teams • Drive solutions toward stable operation with minimal ongoing maintenance

🎯 Requirements

• More than 3 years of solid technical background • Experience as a Solution Engineer, Technical Solutions Engineer, Data Scientist, Data/Systems Analyst, or Technical Project Manager • Proven experience owning projects end-to-end, including scoping, delivery, and stakeholder management • Direct experience working with external customers on technical projects (requirements gathering, delivery, iteration) • Strong Python skills for data manipulation (e.g. NumPy, pandas), natural language processing (e.g. NLTK, spaCy), and building lightweight web services or tools (e.g. FastAPI, Flask) • Solid understanding of ML concepts and data workflows; familiarity with LLMs and prompt engineering is a strong plus • Experience designing multi-stage pipelines and complex systems • Understanding of software development fundamentals: version control, testing, MVPs, iterative development etc. • Bachelor’s or Master’s degree in Data Science, ML/AI, Software Engineering, or a related quantitative field such as Physics or Applied Mathematics, with strong analytical foundations • Ability to reason about trade-offs between quality, speed, cost, and scalability • Excellent English communication skills (B2+), with the ability to explain complex technical concepts to non-technical audiences • Confidence working with data engineers, ML engineers, and researchers from leading tech companies • Strong ownership mindset: comfortable being accountable for outcomes, not just tasks • Ability to manage multiple projects in fast-paced, ambiguous environments

🏖️ Benefits

• Flexible working arrangements

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