Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and scaling AI systems for merchant catalogue automation with an accent on LLM-based enrichment, fine-tuning open-weight models, and agentic workflows. Focus on transitioning from third-party APIs to self-hosted models, optimizing production performance, and driving end-to-end ML solutions from discovery to deployment.

Location: Hybrid role based in Berlin, Germany (minimum 3 days in office per week).

Company

Bolt is a fast-growing European tech company operating in over 50 countries, focused on transforming urban mobility and delivery services.

What you will do

• Design, train, and deploy ML/LLM models for catalogue enrichment, moderation, and categorisation.
• Drive the transition from frontier API models to fine-tuned open-weight models by building data curation and training pipelines.
• Develop agentic AI systems for multi-step catalogue workflows, including tool use and guardrails.
• Build robust evaluation infrastructure, including offline benchmarks, regression suites, and LLM-as-judge pipelines.
• Own the serving and cost optimization for self-hosted models, including throughput tuning and GPU utilization.
• Collaborate cross-functionally with software engineers, data scientists, and product managers to productionise ML solutions.

Requirements

• Proven experience building and shipping ML systems in production at scale.
• Demonstrated track record taking LLM-based systems to production, including evaluation and observability.
• Hands-on experience fine-tuning and serving open-weight models such as LoRA/QLoRA or SFT.
• Deep expertise in NLP or recommendation systems with measurable business impact.
• Mastery of Python and SQL, with production experience using deep learning frameworks like PyTorch, TensorFlow, or JAX.
• Strong product sense and ability to drive ambiguous problems to measurable outcomes.

Culture & Benefits

• Direct role in shaping the future of global mobility and delivery.
• Rewarding salary and stock option package.
• Hybrid working model with a focus on team connection.
• Wellness perks for physical and mental health.
• Opportunities for professional growth in a fast-moving, autonomous environment.