Overview
Founding Engineer, Machine Learning at Stealth — join to apply for this role.
Location: San Francisco, CA
Base pay range
$160,000.00/yr - $200,000.00/yr
About Us
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 + Equity
Additional details
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Engineering and Information Technology
- Industries: Software Development
Referrals increase your chances of interviewing at Stealth. Sign in to set job alerts for “Machine Learning Engineer” roles.
#J-18808-Ljbffr