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Isotron AI

Founding Engineer, Machine Learning

Isotron AI, San Francisco

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Job Description

Job Description

About the Role

We’re an early-stage stealth startup building a new kind of platform for generative media. Our mission is to enable the future of real-time generative applications : we’re building the foundational tools and infrastructure that make entirely new categories of generative experiences and applications finally possible.

We’re a small, focused team of ex-YC and unicorn founders and senior engineers with deep experience across 3D, generative video, developer platforms, and creative tools. We're backed by top-tier investors and top angels, and we're building a new technical foundation purpose-built for the next era of generative media.

We’re operating at the edge of what’s technically possible : high-performance inference and real-time orchestration of multimodal models. As one of our founding engineers, you’ll play a key role in architecting the core platform, shaping system design decisions, and owning critical infrastructure from day one.

If you're excited about architecting and building high-performance infrastructure that empowers the next generation of developers and unlocks entirely new products categories, we’d love to talk.

About the Role

We're looking for a Founding Machine Learning Engineer to build the core infrastructure powering high-performance inference for generative media models, including diffusion and transformer architectures. You’ll be instrumental in designing low-latency, high-throughput systems that serve state-of-the-art models in real time. As an early technical leader, you'll shape both our systems and culture from day one.

What You’ll Do

  • Architect and implement the inference engine for diffusion transformer-based generative models
  • Optimize model execution across the stack — memory, compute, and networking
  • Drive performance engineering to minimize latency and maximize throughput
  • Work closely with research to productionize new generative techniques and model variants
  • Build the tools, services, and monitoring that make these systems robust and scalable
  • Set the technical bar and help define engineering culture as an early team member

Requirements

About You

  • 3+ years of experience building high-performance ML or systems infrastructure
  • Deep fluency with PyTorch and production-grade Python
  • Strong understanding of GPU systems (CUDA, memory hierarchies, scheduling, etc.)
  • Experience optimizing inference for generative models (e.g., diffusion, transformers)
  • Bonus : Familiarity with Triton, CUDA, TensorRT, or model parallelism techniques
  • Startup-ready : you take ownership, move quickly, and solve hard problems end to end
  • Minimum Qualifications

  • Strong Python + PyTorch skills
  • Proven experience optimizing inference for generative models
  • Deep systems knowledge, especially GPU performance tuning
  • High agency and eagerness to build from scratch
  • Benefits

  • Competitive SF salary and foundational team equity
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