AI Data Engineering Lead

ZipRecruiter; London; Remote; GBP 60,000 - 90,000; Full time

Job summary

A pioneering AI company is seeking a Data Engineer to build and scale machine learning training pipelines, focusing on video datasets. Join a remote-first team that values technical excellence and creative innovation, and help shape the future of AI.

Qualifications

• Deep experience with ML data pipelines.
• Expertise with petabyte-scale datasets, ideally video-heavy.

Responsibilities

• Own and scale ML training pipelines.
• Architect ingestion systems and build scalable data infrastructure.
• Curate datasets from messy, unstructured sources.

Skills

ML data pipelines

Cloud infrastructure

Data quality metrics

Tools

Terraform

Kubernetes

AWS

GCP

Azure

Job description

Job Description

We’re partnering with a next- AI company that’s reshaping the future of ML and media - blending deep tech with creative excellence. After a series of strategic acquisitions and partnerships, their growth trajectory is steep, and they’re building a best-in-class technical team to scale even faster.

Right now, Data Engineering is their #1 priority.

They’re actively hiring for:

• Data Engineer
• Lead / Head of Data Engineering

About the Company:

• Remote-first culture (timezone-flexibility is key)
• Backed by top investors and industry leaders
• Recently acquired a film studio and partnered with a key player in creative AI
• Hardcore belief in combining technical excellence with creative innovation

Why They’re Hiring: Their AI researchers and scientists are stretched thin, pulled into building foundational data pipelines when they should be focused on modeling. They're standing up a dedicated Data Engineering team - and they need top talent now to scale their machine learning efforts, especially around video-based models.

What You'll Work On:

• Own and scale ML training pipelines (think video datasets at petabyte scale)
• Curate datasets from messy, unstructured sources - with a focus on automation
• Architect ingestion systems and build scalable data infrastructure
• Partner deeply with Infra, AI Research, and Product teams
• Play a key role supporting projects like foundational model development and synthetic data

Tech Stack & Must-Have Skills:

• Deep experience with ML data pipelines
• Cloud infrastructure: Terraform, Kubernetes, AWS/GCP/Azure
• Expertise with petabyte-scale datasets, ideally video-heavy
• Knowledge of distributed systems and ML data workflows
• Strong intuition for data quality metrics and ML- thinking

Bonus Points For:

• Visual Model (VLM) experience
• Building ML classifiers for data evaluation
• Automated quality control in training pipelines
• Familiarity with AI media and synthetic data tools

What They’re Looking For:

• Systems thinkers who can build and own at scale
• Startup hustle combined with Big Tech polish (Meta, Google, etc.)
• Experience leading roadmaps and building from zero to one
• People who thrive in ambiguity, ownership, and operating without hand-holding

The Process:

• Initial Call: 30 minutes (schedule-friendly, quick turnaround)
• Technical Deep-Dive: 90 minutes with an engineering leader
• Coding Interview: Hands-on session
• Final Chat: With the CEO and/or CSO

They move fast - and will fast-track standout candidates.

Ready to step into a critical role where your work will directly shape the future of AI?