Senior Machine Learning Engineer – Delivery Merchant

About the role

As a Senior Machine Learning Engineer you will own and scale AI systems that power Bolt Food's merchant catalogue and opportunity sizing across more than 50 markets. You will move from ambiguous business problems through offline evaluation, online experiments and production, shaping the technical direction of our catalogue automation.

Key responsibilities

• Design, train and deploy ML/LLM models for catalogue enrichment, moderation and categorisation, managing accuracy, latency and cost.
• Lead the transition from third‑party API models to fine‑tuned open‑weight models, building data curation and fine‑tuning pipelines.
• Develop agentic AI systems for multi‑step catalogue workflows, including tool use, guardrails and evaluation harnesses.
• Build evaluation and experimentation infrastructure such as offline benchmarks, regression suites, LLM‑as‑judge pipelines and A/B tests tied to business metrics.
• Own serving and cost optimisation for self‑hosted models, handling quantisation, throughput tuning and GPU utilisation.

Required profile

• Proven experience shipping ML systems at scale in consumer‑facing tech products.
• Track record taking LLM‑based systems to production with prompt iteration, evaluation, guardrails and cost management.
• Hands‑on experience fine‑tuning and serving open‑weight models (e.g., LoRA/QLoRA, SFT, preference optimisation).
• Deep expertise in NLP or recommendation systems that have moved a business metric.
• Strong product sense, proactive ownership and ability to turn ambiguous problems into measurable ML solutions.

Required skills

• Python
• SQL
• PyTorch, TensorFlow, JAX or Triton
• AWS, SageMaker
• Airflow
• Docker
• LLM development and prompting
• LoRA / QLoRA fine‑tuning
• SFT and preference optimisation
• GPU utilisation and quantisation

What we offer

• Direct impact on millions of customers and partners across 850+ cities.
• Fast‑moving autonomous teams with supportive colleagues.
• Professional growth through unique career opportunities.
• Competitive salary and stock‑option package.
• Hybrid working model with at least three days in the office.
• Wellness perks supporting physical and mental health.