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Tech Stack
Tools & technologiesPythonPyTorchTensorflow
About the role
Key responsibilities & impact- Integrate TensorRT-LLM for BioNeMo models.
- Optimize models for low-latency, high-throughput inference.
- Profile and debug deep learning workloads on GPUs.
- Develop and validate custom GPU kernels for hot paths.
- Collaborate with research to align model architecture and training.
Requirements
What you’ll need- MS/PhD in CS, EE, Comp. Eng., or equivalent practical experience.
- 5+ years professional experience in deep learning/applied ML.
- Strong foundation in transformer/diffusion architectures.
- Direct experience with LLMs, VLMs, or large biology models.
- Proficient in PyTorch and/or TensorFlow.
- Strong Python/C++ skills.
- Practical experience with TensorRT/TensorRT-LLM.
Benefits
Comp & perks- Health insurance
- Professional development
- Flexible working hours
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
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Hard Skills & Tools
deep learningapplied MLtransformer architecturediffusion architectureLLMsVLMsPyTorchTensorFlowPythonC++
Certifications
MSPhD
