[Hiring] Staff Deep Learning Compiler Engineer @quadric

Role Description

Quadric is building the world’s first General-Purpose Neural Processing Unit (GPNPU) architecture, bringing high-performance AI, DSP, and ML compute to edge devices. As a Deep Learning Compiler Engineer, you will design and optimize the compiler stack (MLIR, TVM, LLVM) that bridges state-of-the-art neural network frameworks directly to our proprietary hardware architecture. You'll play a critical role in unlocking peak hardware performance, low latency, and memory efficiency for edge AI workloads.

What You'll Do

• Deep Learning Compiler Infrastructure & Optimization
  • Design, implement, and maintain compiler optimization passes targeting Quadric’s processor architecture using frameworks like MLIR, Apache TVM, or LLVM.
  • Develop lowering pathways from high-level machine learning frameworks (PyTorch, TensorFlow, ONNX) down to optimized low-level kernel code.
  • Optimize neural network performance for memory throughput, latency, compute unit utilization, and power consumption.
• Neural Network Model Parsing & Graph Transformation
  • Implement graph-level optimizations, including operator fusion, layout transformation, quantization (INT8/FP16), and memory allocation strategies.
  • Analyze novel deep learning model topologies (Transformers, CNNs, 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.
• Hardware-Software Co-Design
  • Collaborate closely 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.

What Success Looks Like

Within your first 6–12 months, you'll:

• Successfully integrate support for key deep learning models (e.g., modern Transformer architectures or Vision models) into Quadric's compiler pipeline.
• Implement custom graph and codegen optimization passes that deliver measurable performance improvements on target benchmarks.
• Partner with the architecture team to influence the next-generation micro-architecture definition through data-driven workload analysis.

Qualifications

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

Preferred

• Experience with low-level kernel optimization, SIMD/vector programming, and memory allocation strategy development.
• Knowledge of model quantization methodologies (INT8, FP8, mixed-precision) and post-training/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.

Benefits

• Medical, dental, and vision insurance from day one - Premiums covered at 99% for Employees.
• Company-paid life Insurance.
• Voluntary supplemental life insurance.
• STD + LTD insurance.
• Commuter support including parking or Caltrain reimbursement. Our office is conveniently located within walking distance of the Caltrain station.
• FSA + HSA.
• Equity with the business.
• Paid Parental Leave.
• 401(k) Retirement Plan.
• Flexible PTO.
• Winter holiday shutdown.
• Catered lunch each day in our office.
• Downtown Burlingame office location, close to shops, cafes, and local amenities.
• Collaborative, low-ego culture with significant ownership and impact.
• A work culture focused on innovative disruption.