Staff Machine Learning Engineer, AI Applications, Tallinn

Requirements

• You have hands-on experience with retrieval-augmented systems, search, ranking, or knowledge-based AI applications, and understand what drives high-quality grounded responses.
• You have worked on knowledge-heavy or policy-constrained domains where correctness, consistency, and trust matter.
• You have experience building feedback loops from user behavior, QA signals, annotations, or operational outcomes into system improvements.
• You are able to operate at both strategic and hands-on levels: defining long-term direction while also diving into data, experiments, and failure analysis.
• You have strong communication and stakeholder management skills, and can align engineering, product, and operations around quality strategy and trade-offs.
• Experience with LLM-based pipelines or agentic AI systems is a strong plus, especially in areas such as tool use, routing, memory, multi-step reasoning, or human-AI orchestration.

What You'll Be Doing

• Lead alignment of Customer Support AI system behavior to Bolt’s business goals, customer experience standards, and policy requirements, improving answer quality, consistency, grounding, and escalation behavior.
• Build and scale knowledge mining capabilities that turn conversations, support tickets, workflows, policies, and operational data into reusable knowledge assets and improvement signals.
• Own the evaluation strategy for LLM-powered customer support systems, including offline benchmarks, golden datasets, human review workflows, online experimentation, and production quality metrics.
• Develop feedback loops that connect production failures and human corrections back into prompts, retrieval, benchmarks, and model behavior, enabling continuous improvement of automation quality.
• Partner closely with engineers working on AI application infrastructure, contributing ML expertise to areas such as tool-use quality, routing behavior, memory quality, and multi-step task performance.
• Influence roadmap and technical direction across teams by bringing clarity to trade-offs in model behavior, retrieval quality, experimentation, and business impact.

Nice to Haves

• Experience with LLM-based pipelines or agentic AI systems is a strong plus, especially in areas such as tool use, routing, memory, multi-step reasoning, or human-AI orchestration.

Perks and Benefits

• Play a direct role in shaping the future of mobility.
• Impact millions of customers and partners in 600+ cities across 50+ countries.
• Work in fast-moving autonomous teams with some of the smartest people in the world.
• Accelerate your professional growth with unique career opportunities.
• Get a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of working in a hybrid mode with a minimum of 2 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.