Senior Software Engineer, Quantized Inference
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
+2 more
Job description
We are now looking for a Senior Software Engineer for Quantized Inference! NVIDIA is seeking software engineers to accelerate the discovery and deployment of efficient inference recipes for LLMs. A recipe defines which operators are transformed into low-precision or sparsified variants - unlocking throughput and latency gains without regressing accuracy or verbosity. Recipes may incorporate techniques such as rotations, block scaling to attenuate outlier impact, or improved calibration data drawn from SFT/RL pipelines.
Each new recipe demands corresponding kernel and model-level implementations in inference engines (vLLM, TRT-LLM, SGLang). The candidate will translate recipe specifications into functionally correct, performant code, e.g., writing Triton kernels, inserting quantize/dequantize nodes into prefill and decode paths, and ensuring per-expert scaling in MoE layers is handled correctly. From there, the candidate will collaborate with partner inference teams to further optimize throughput and interactivity on target workloads. This work is a core component of our productization effort across Megatron-LM, ModelOpt, and vLLM.
What you’ll be doing:
-
Implement quantized and sparse recipes in inference engines (vLLM, TRT-LLM, SGLang)
-
Own model export pipelines (ModelOpt, Megatron-LM <-> HuggingFace), ensuring quantized checkpoints serialize correctly for downstream serving
-
Build prototypes and benchmarking harnesses to evaluate recipe throughput/interactivity before full optimization
-
Develop data analysis tooling and visualizations for numerics debugging
-
Improve developer productivity across the team: CI, build systems, training infrastructure, pipeline friction
Requirements
- Proficient in Python; familiarity with C+
+
-
Strong software engineering fundamentals: concise, well-tested code; fluent with AI-assisted tooling
-
Experience with ML accelerators with a basic understanding of how certain ML layers affect execution time
-
Familiarity with PyTorch internals (custom ops, autograd, export) or equivalent framework
-
Experience reading, modifying, or contributing to a large open-source codebase
-
MS/PhD in Computer Science or related field, or equivalent experience.
-
4+ years in a relevant software engineering role
-
Demonstrated ability to move fast with ambiguous requirements, with strong written and verbal communication
Ways to stand out from the crowd:
-
Experience contributing to inference serving frameworks (vLLM, TRT-LLM, SGLang) or Triton kernel development
-
Track record of debugging numerical issues across mixed-precision boundaries
-
Deep experience with model compression techniques: PTQ, QAT, structured/unstructured sparsity
Benefits & conditions
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Apply on www.juju.comGood distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence
The Fastest-Growing Tech Sectors to Look Out for in 2025
MLOps And AI Driven Development
How to Become an AI Engineer