Staff Deep Learning Compiler Engineer

quadric

8d • $170,000 - $230,000

About The Position

Quadric is building a General-Purpose Neural Processing Unit (GPNPU) for high-performance AI, DSP, and machine-learning compute on edge devices. The Staff Deep Learning Compiler Engineer will design and optimize the compiler stack—including MLIR, Apache TVM, and LLVM—to connect neural-network frameworks with Quadric’s proprietary hardware. The role focuses on delivering high performance, low latency, and memory efficiency for edge AI workloads.

The engineer will develop compiler infrastructure and optimization passes, build lowering pathways from frameworks such as PyTorch, TensorFlow, and ONNX to low-level kernels, and optimize model performance across memory throughput, latency, compute utilization, and power consumption. The role also involves graph transformations and support for evolving model architectures, as well as profiling and benchmarking end-to-end workloads.

Working closely with hardware and micro-architecture teams, the engineer will contribute to instruction-set and accelerator-feature definition, validate compiler correctness and generated-binary performance with simulators and test benches, and participate in FPGA and ASIC bring-up and validation. Success includes integrating support for key deep-learning models, delivering measurable optimization improvements, and using workload analysis to inform future micro-architecture decisions.

Requirements

• BS, MS, or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
• 8+ years of hands-on experience developing deep-learning compilers or compiler infrastructure, such as MLIR, Apache TVM, LLVM, XLA, TensorRT, or Glow.
• Strong proficiency in C++ (14/17/20) and Python.
• Solid fundamentals in data structures, algorithms, and object-oriented design.
• Familiarity with modern AI/ML frameworks such as PyTorch, TensorFlow, and ONNX, and with deep-learning operator representations.
• Solid understanding of computer systems, memory hierarchies, parallel processing, and CPU/GPU/NPU instruction execution.

Nice To Haves

• Experience with low-level kernel optimization, SIMD/vector programming, and memory-allocation strategy development.
• Knowledge of model quantization methodologies, including INT8, FP8, and mixed precision, and post-training or QAT optimization techniques.
• Prior experience working on software stacks for custom AI accelerators, DSPs, or embedded architectures.
• Experience with FPGA bring-up, hardware emulation, or cycle-accurate simulator development.

Responsibilities

• Design, implement, and maintain compiler optimization passes targeting Quadric’s processor architecture using MLIR, Apache TVM, LLVM, or related frameworks.
• Develop lowering pathways from high-level machine-learning frameworks such as PyTorch, TensorFlow, and ONNX to optimized low-level kernel code.
• Optimize neural-network performance for memory throughput, latency, compute-unit utilization, and power consumption.
• Implement graph-level optimizations, including operator fusion, layout transformation, quantization, and memory-allocation strategies.
• Analyze deep-learning model topologies, including Transformers, CNNs, and Vision-Language Models, and extend compiler support for new operators and primitives.
• Benchmark and profile end-to-end model performance to identify and resolve compiler bottlenecks.
• Collaborate with hardware and micro-architecture teams to define instruction-set extensions, hardware-acceleration features, and compiler requirements.
• Develop software simulators, functional models, and test benches to validate compiler correctness and generated-binary performance.
• Participate in hardware bring-up and validation efforts on FPGA and ASIC platforms.
• Integrate support for key deep-learning models into Quadric’s compiler pipeline and implement optimization passes that improve target benchmarks.
• Use data-driven workload analysis to help shape next-generation micro-architecture.

Benefits

• Medical, dental, and vision insurance from day one, with premiums covered at 99% for employees.
• Company-paid life insurance.
• Voluntary supplemental life insurance.
• Short-term and long-term disability insurance.
• Commuter support, including parking or Caltrain reimbursement.
• Flexible spending account (FSA) and health savings account (HSA).
• Equity.
• Paid parental leave.
• 401(k) retirement plan.
• Flexible PTO.
• Winter holiday shutdown.
• Catered lunch each day in the office.
• Collaborative culture with significant ownership and impact.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior