āØ AI Insights & Summary
Bolt is seeking a Staff Machine Learning Engineer to revolutionize its Customer Support AI Applications, focusing on enhancing quality, learning, and knowledge foundations. This high-impact role offers the chance to shape AI evaluation, improve retrieval systems, and build continuous feedback loops for customer support automation. If you're passionate about applied ML, knowledge systems, and making AI products demonstrably better in production, this is a unique opportunity to influence the future of a rapidly growing global tech company.
About Bolt
Bolt is one of Europe and Africa's fastest-growing tech companies, serving over 200 million customers in 50+ countries. We are committed to creating an inclusive environment where everyone is welcome. Our mission is to make cities for people, not cars, and we are looking for talented individuals to help us achieve this.
About the Role
As a Staff Machine Learning Engineer, you will work at the intersection of advanced AI, knowledge systems, and Bolt's production support ecosystem. You will set the technical direction for measuring, improving, and scaling AI quality across conversational experiences, ensuring our systems are accurate, helpful, grounded, and aligned with business and customer needs. This is a high-impact, high-scope role where you will define the quality and learning strategy behind our AI systems, partner closely with engineering, product, operations, and domain experts, and translate real-world support interactions into durable improvements across models, retrieval, and workflows.
Main tasks and responsibilities:
- Lead the 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 transform 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.
- We are not primarily looking for Node.js experts, but for cross-language engineers for whom a specific stack is just a tool to solve a problem, not the solution itself.
About you:
- 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 in knowledge-heavy or policy-constrained domains where correctness, consistency, and trust are paramount.
- You have experience building feedback loops from user behavior, QA signals, annotations, or operational outcomes into system improvements.
- You can operate at both strategic and hands-on levels: defining long-term direction while also diving into data, experiments, and failure analysis.
- You possess strong communication and stakeholder management skills, able to align engineering, product, and operations around quality strategy and trade-offs.
- Experience with LLM-based pipelines or agentic AI systems is a strong plus, particularly in areas such as tool use, routing, memory, multi-step reasoning, or human-AI orchestration.
Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don't tick every box, please consider applying if you feel you're the kind of person described above!
Why you'll love it here:
- 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.
- Receive a rewarding salary and stock option package.
- Enjoy the flexibility of working in a hybrid mode with a minimum of 2 days in the office each week.
- Take care of your physical and mental health with our wellness perks.
- Some perks may differ depending on your location and role.