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About the Role
As a Research Engineer focused on Generative AI Deployment, you will own the path from research to production for the neural and generative models that power Waabi World, our multi-sensor simulator. You will partner with research teams on models such as feed-forward scene reconstruction models, diffusion models, and vision foundation models. Your job is to make those models production ready: fast, memory-efficient, reproducible, and numerically trustworthy at the scale of closed-loop simulation.
Responsibilities
- Be part of a multidisciplinary team of Research Scientists and Engineers building a best-in-class multi-sensor simulation stack.
- Take cutting-edge models from research to production. Turn research code and checkpoints into versioned, reproducible, exportable production models.
- Make generative models leaner and faster to run by profiling end to end and applying optimization techniques.
- Own correctness as part of performance by building benchmarks and numerical-parity tests.
- Build shared deployment tooling for export, versioning, model registry, and builds.
- Shape models for deployment by working with research scientists early on architecture design.
Requirements
- Experience reading and developing production-quality software at scale, not just prototypes.
- Shipped ML systems that other engineers and researchers depend on daily.
- Experience taking models from a research codebase to an optimized production artifact, measuring speedup and accuracy change.
- Hands-on experience with TensorRT, torch.compile, torch.export, ONNX, post-training quantization, quantization-aware training, and pruning.
- Experience handling models with custom CUDA operators or other operations that do not export cleanly.
- Experience profiling with tools such as Nsight Systems, Nsight Compute, and the PyTorch profiler.
- Ability to reason about memory bandwidth, kernel launch overhead, and host-device synchronization.
- Ability to write or modify CUDA or Triton kernels.
- Ability to read research code for modern architectures and identify compute/memory bottlenecks.
- Knowledge of accuracy trade-offs when lowering precision, compiling models, or reducing sampling steps.
- Experience launching and debugging GPU jobs in the cloud (AWS, GCP, or equivalent).
- Experience with job orchestration, containerized environments, and maintaining version compatibility for CUDA, PyTorch, and TensorRT.
Skills
- Generative AI Deployment
- Neural Models
- Generative Models
- Feed-forward scene reconstruction models
- Diffusion models
- Vision foundation models
- Model optimization
- Model deployment
- TensorRT
- torch.compile
- torch.export
- ONNX
- Post-training quantization
- Quantization-aware training
- Pruning
- CUDA
- Triton kernels
- Nsight Systems
- Nsight Compute
- PyTorch profiler
- Vision transformers
- Flow-matching models
- Cloud Infrastructure (AWS, GCP)
- Job orchestration
- Containerized environments
Location
- Toronto
- San Francisco
- Dallas
- Pittsburgh
Work Type
- Full-time
- Work from Home support
Experience Level
- Production Software
- ML Systems
- Model Optimization and Deployment
- GPU Performance
- Cloud Infrastructure
Salary/Compensations
- $200,000 - $275,000 USD
Benefits
- Competitive compensation and equity awards
- Medical, Dental and Vision coverage (for full-time employees only)
- Unlimited Vacation
- Flexible hours
- Work from Home support
- Daily drinks, snacks and catered meals (when in office)
- Regularly scheduled team building activities and social events
About the Company
- Waabi is a technology start-up building technologies to transform the way the world moves.
- Join our talented team to be a part of the future and to make an impact!
Equal Opportunity
- Waabi is an equal opportunity employer.
- We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees.
- We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law.
- We make workplace accommodations for qualified individuals with disabilities as required by applicable law.
- If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.