Senior Machine Learning Engineer, Delivery Merchant

We're looking for a Senior Machine Learning Engineer to own and scale the AI systems behind Bolt Food's merchant catalogue and opportunity sizing systems, spanning LLM-based enrichment and categorisation through to fine-tuned open-weight models we train and serve ourselves, all in service of automating merchant operations across 50+ markets.

About Us With over 200 million customers across 50+ countries and 850+ cities, Bolt is one of the fastest-growing tech companies in Europe and Africa — powered by 4.5+ million partners on our platform, 4,000+ employees globally.

And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, national origin, age, or ability.

Our ultimate goal is to make cities for people, not cars — and we need your help on this mission!

About The Role You'll join the Delivery Merchant engineering group alongside software engineers, product managers, and data scientists who build the systems our merchant partners depend on.

Your mission is to make our ML-powered catalogue automation substantially better by raising model quality, hardening services into reliable production systems, and extending into new areas like agentic catalogue workflows and merchant scoring.

There's also a significant frontier here.

Today we rely heavily on third-party API models.

You'll help drive our transition to fine-tuned open-weight models we own and serve ourselves, giving us better economics, lower latency, and more control.

This is early-stage, high-leverage work where you'll shape the technical direction.

This is a hybrid, end-to-end role.

You'll work from ambiguous business problems through offline evaluation, online experiments, and production systems, and you'll stay accountable for the outcomes.

About The Role You'll join the Delivery Merchant engineering group alongside software engineers, product managers, and data scientists who build the systems our merchant partners depend on.

Your mission is to make our ML-powered catalogue automation substantially better by raising model quality, hardening services into reliable production systems, and extending into new areas like agentic catalogue workflows and merchant scoring.

There\'s also a significant frontier here.

Today we rely heavily on third-party API models.

You'll help drive our transition to fine-tuned open-weight models we own and serve ourselves, giving us better economics, lower latency, and more control.

This is early-stage, high-leverage work where you'll shape the technical direction.

This is a hybrid, end-to-end role.

You'll work from ambiguous business problems through offline evaluation, online experiments, and production systems, and you'll stay accountable for the outcomes.

• Main Tasks And Responsibilities
• Design, train, and deploy ML/LLM models that automate catalogue enrichment, moderation, and categorisation at scale, owning accuracy, latency, and cost in production.
• Drive the transition from frontier API models to fine-tuned open-weight models: build data curation and fine-tuning pipelines, run quality comparisons, and take winners into production.
• Design and build agentic AI systems for catalogue automation, covering multi-step workflows, tool use, guardrails, and the evaluation harnesses to prove they work.
• Build evaluation and experimentation infrastructure: offline benchmarks, regression suites, LLM-as-judge pipelines, and A/B tests tied to business metrics.
• Own the serving and cost story for self-hosted models, including quantisation, throughput tuning, GPU utilisation, and build-versus-buy decisions.
• Collaborate cross-functionally with Software Engineers, Data Scientists, Product Managers, and the ML Platform team to productionise and monitor ML solutions.

About You

• Proven experience building and shipping ML systems in production at scale, ideally in consumer-facing product environments at a technology company.
• Demonstrated track record taking LLM-based systems to production, including prompt/model iteration, evaluation, guardrails, observability, and cost management.
• Hands-on experience fine-tuning and serving open-weight models (e. g.

Lo RA/QLo RA, SFT, preference optimisation), including building training data and managing production serving.

• Deep expertise in NLP or recommendation systems, with models that have moved a business metric.
• Strong engineering fundamentals: mastery of Python and SQL, clean code practices, production experience with a deep learning framework (Py Torch, Tensor Flow, JAX, or Triton), and experience with modern ML tooling and cloud infrastructure (AWS, Sage Maker, Airflow, Docker).
• Strong product sense and proactive ownership, with the ability to turn ambiguous problems into measurable ML solutions and drive them from discovery to production impact.

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!

• Why you\'ll love it here
• Play a direct role in shaping the future of mobility.
• Make an impact on millions of customers and partners across 850+ cities in 50+ countries.
• Work in fast-moving, autonomous teams with talented and supportive colleagues.
• Accelerate your professional growth with unique career opportunities.
• Receive a rewarding salary and stock option package that lets you focus on doing your best work.
• Enjoy the flexibility of hybrid working, with a minimum of 3 days in the office each week to foster strong connections and teamwork.
• Take care of your physical and mental health with our wellness perks.

Some perks may differ depending on your location and role.

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