We’re partnering with a next-generation 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 generation
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-native thinking
Bonus Points For:
- Visual Language 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?
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