ML Compiler Engineer
San BrunoFull timePosted 3mo ago
About the role
You will work on a custom ML compiler that transforms modern ML and DSP models into highly efficient programs for femtoAI's accelerator, spanning the full compiler stack from model ingestion to optimization under tight memory and latency constraints.
Responsibilities
- Build and maintain model ingestion pipelines (e.g., PyTorch / ONNX → internal IR)
- Implement graph transformations such as:
- Operator decomposition and canonicalization
- Shape inference and layout transformations
- Develop and extend intermediate representations (e.g., MLIR)
- Implement optimization passes including:
- Operator fusion and graph partitioning
- Basic scheduling and tiling strategies
- Memory planning and reuse
- Debug correctness and numerical issues across transformations
- Collaborate with hardware and ML teams to improve system performance
Qualifications
- 2+ years of experience in compilers and/or edge-AI
- Proficiency in Python and/or C++
- Experience with at least one: MLIR, LLVM, TVM, XLA, or similar
- Graph-level transformations or ML model internals
- Understanding of deep learning models (conv, sequence models, etc.)
- Ability to reason about correctness and performance tradeoffs
Skills
Required:Compiler developmentPythonC++MLIR / LLVM / TVM / XLAGraph transformationsDeep learning models
Benefits
- 401(k)
- Medical insurance
- Vision insurance
- Dental insurance
- Commuter benefits
- Disability insurance
- Paid maternity leave
- Paid paternity leave
- Child care support
Last updated Oct 4, 2026. Interested? Apply on the company site.
About femtoAI
AI Inference for the Extreme Edge
AI Inference platform for edge devices enabling higher performance at lower latency with ultra-low power in compact silicon.
AI acceleratorEmbedded AI PlatformNeuromorphic computingSPUSparse Processing Unitbessemer-ai-infrastructure-2026edge AIinference-inflection-point
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