Machine Learning Prototyping Engineer

Overview

The Job title: Machine Learning Prototyping Engineer

The Project duration: 6 months

The Project location: UK ( London )

Working pattern of the role (Hybrid , Remote, full time onsite): Hybrid ( 3 days WFO )

Responsibilities

• Take loosely defined problems and turn them into proofs of concepts (PoCs) within days.
• Combine data engineering, modelling and lightweight application development to test ideas end-to-end.
• Where a PoC shows promise, grow it into a prototype (applying the concept to functional business needs) within 2-3 weeks.
• Work independently with minimal guidance and iterate quickly based on feedback and communicate results clearly.

Qualifications

• Strong ability to translate ideas into working solutions quickly.
• Hands-on skills across:
  • Python (data processing, ML, prototyping).
  • Data engineering (APIs, data pipelines, SQL, cloud data).
  • Lightweight app development (APIs, simple frontends, notebooks, dashboards).
• Solid (not necessarily extensive) knowledge of the statistical/mathematical fundamentals that support and proposed ML methodologies.
• Experience building end-to-end prototypes, not just models.
• Comfortable working in ambiguous, fast-moving environments.
• Strong problem-solving and independent thinking.

Nice to have

• Experience integrating LLMs or AI services into applications.
• Familiarity with modern data platforms (e.g. Snowflake).
• Experience with visualisation tools (e.g. Tableau, Plotly).
• Working knowledge of marketing and advertising.

What success looks like

• You can go from idea -> working PoC in 2–3 days.
• You can go from working PoC to useful prototype in 2–3 weeks.
• You unblock decisions by demonstrating feasibility quickly.
• You focus on practical outcomes, not perfect code.

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