Cubiq Recruitment · 4 weeks ago
Staff ML Infrastructure Engineer
San Francisco Bay Area
Full-time
Onsite
Lead/StaffCubiq Recruitment is building one of the world’s leading generative video and multimodal AI platforms, and they are seeking a Staff ML Infrastructure Engineer. This role involves designing and evolving infrastructure for large-scale generative video and multimodal model training, as well as ensuring production reliability and developing end-to-end CI/CD pipelines for machine learning.
Artificial Intelligence (AI)AutomotiveAutonomous VehiclesEmerging MarketsEnergyHealth CareMachine LearningManufacturingRenewable EnergySoftware
Hiring Manager
Jack Cartlidge
Responsibilities
Core ML Platform Architecture: Design and evolve the infrastructure that supports large-scale generative video and multimodal model training, evaluation, and deployment
High-Throughput Compute Systems: Build and optimize GPU/TPU clusters, distributed training systems, and orchestration layers tailored for video-heavy pipelines
Production Reliability for Generative Models: Create the tooling and services needed to safely push frequent model updates while handling massive compute loads and long-running jobs
End-to-End CI/CD for ML: Lead the development of automated pipelines for model training, validation, artifact management, and production rollout
Multimodal Data Infrastructure: Build systems to ingest, version, transform, and serve large-scale video, audio, and text datasets with high reliability
Internal Developer Experience: Partner with research, product, and applied ML teams to build intuitive internal tooling for experiment tracking, model lineage, and resource scheduling
Technical Leadership: Mentor engineers, set platform standards, and influence long-term architectural direction
Qualification
Required
Experience architecting and operating large-scale infrastructure at a cloud provider, hyperscaler, or leading AI company
Built or owned mission-critical CI/CD systems, high-capacity compute platforms, or data infrastructure supporting ML teams
Deep experience with distributed compute across GPUs/accelerators, Kubernetes, and cloud infrastructure (AWS/GCP/Azure)
Strong engineering fundamentals in Python, Go, or equivalent languages
Previous exposure to ML training pipelines—especially systems that handle heavy video, multimodal, or high-dimensional data
Demonstrated ability to lead complex cross-org initiatives and drive technical strategy
Preferred
Experience with video processing systems, large-scale media pipelines, or streaming architectures
Familiarity with modern multimodal or video-generation frameworks (PyTorch, JAX, diffusers, custom accelerators)
Experience with Ray, Triton, CUDA optimization, or specialized scheduling for ML workloads
Background working in high-growth AI startups or research-focused environments
Security and compliance considerations for models that generate or process user content
Benefits
Over market average
Equity
Highly competitive compensation
Company
Cubiq Recruitment
Cubiq are a talent partner who specialise in niche areas of Technology & Engineering.
Founded in 2010
11-50 employees
Funding
Current Stage
Early StageRecent News
The Business Desk
2023-12-25
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