Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and maintaining data foundations for multimodal agent research with an accent on scalable pipelines, dataset curation, and ML infrastructure. Focus on designing efficient training loops, implementing human-in-the-loop annotation workflows, and ensuring high-quality data for LLM/VLM fine-tuning.

Location: Must be based in London, UK (Hybrid work model).

Company

A global design platform empowering millions to create with confidence through magical AI-driven tools.

What you will do

• Design and build scalable data pipelines for agent training, including collection, filtering, and versioning.
• Maintain infrastructure for efficient data loading and storage using cloud and distributed systems.
• Collaborate with research scientists to translate requirements into concrete data specifications.
• Develop tooling for human annotation workflows and synthetic data generation.
• Establish data quality frameworks, monitoring for drift and contamination to ensure reproducibility.
• Implement comprehensive test coverage for data pipelines and ML workflows.

Requirements

• Strong software engineering skills in Python with experience in production-grade data pipelines.
• Practical experience with prompt engineering for LLM/VLM outputs.
• Hands-on experience with large-scale data processing, versioning, and distributed ML training.
• Familiarity with annotation tooling and human-in-the-loop data collection.
• Deep understanding of ML training requirements for fine-tuning models.
• Experience working with cloud infrastructure (AWS) and distributed storage.

Nice to have

• Experience with preference data collection for RLHF or reward modelling.
• Familiarity with multimodal data such as image-text pairs and video.
• Background in data quality metrics and monitoring systems.

Culture & Benefits

• Equity packages to share in company success.
• Inclusive parental leave policy for all parents and carers.
• Annual Vibe & Thrive allowance for wellbeing and office setup.
• Flexible leave options to support personal recharge and social impact.
• Access to a vibrant campus environment with provided meals and collaborative workspaces.