🛠 Tech Stack

💼 About This Role

You'll build and own the systems that turn raw real-world data into trained world models and reliable production endpoints for a generative 3D AI company. You will design, implement, and operate scalable training stacks, data ingestion pipelines, and model serving, working closely with the research team in a hands-on, code-heavy role. This is a unique opportunity to shape the infrastructure for next-generation world models.

🎯 What You'll Do

• Own and evolve ML systems for training, evaluation, and serving of large foundation models.
• Improve distributed training stacks (PyTorch DDP/FSDP) for performance and stability.
• Build end-to-end data pipelines for ingestion, preprocessing, and storage at petabyte scale.
• Operate ML workflow orchestration and model serving platforms (Kubeflow, Airflow, Modal).
• Manage containerization, IaC (Terraform), and CI/CD for GPU workloads.

📋 Requirements

• 3+ years writing production-quality Python in a large codebase.
• Hands-on with modern ML training stacks (PyTorch, DDP/FSDP) and debugging distributed jobs.
• Shipped end-to-end data pipelines at scale with real-world sources.
• Proficient with containers (Docker, Kubernetes) and IaC (Terraform).

✨ Nice to Have

• Experience with ML workflow orchestration (Kubeflow Pipelines, Airflow) and experiment tracking (MLflow).
• Knowledge of observability tooling (Prometheus/Grafana, OpenTelemetry).

🎁 Benefits & Perks

• 🏖️ Flexible time off
• 💰 Equity package
• 🧠 Learning budget
• 🏢 Central London office
• 🍽️ Daily lunch provided

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Final Round· 45 min