Senior Tech Lead Manager, Model Efficiency
CohereSalary not specified
- Full Time
- Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine Learning, HardwareIndustries
Requirements
Candidates must have a Bachelor's degree in Computer Science with at least 7 years of relevant industry experience, or a Master's degree in Computer Science with at least 5 years of relevant industry experience. Proficiency in delivering production quality code in modern C++ is required, along with experience in modern compiler infrastructures such as LLVM or MLIR. Familiarity with machine learning frameworks and interfaces like ONNX, TensorFlow, and PyTorch is essential, as well as experience in production compiler development. Preferred qualifications include algorithm design skills and experience with relevant Open Source ML projects like Torch-MLIR, ONNX-MLIR, Caffe, or TVM.
Responsibilities
The ML Compiler Engineer will develop the compiler backend, focusing on the assignment of hardware resources in a spatial architecture to execute low-level instructions. The role involves solving algorithmic compiler problems and learning the intricate details of the underlying hardware and software architectures. The engineer will work on model partitioning, tiling, resource allocation, memory management, scheduling, and optimization for latency, bandwidth, and throughput while collaborating with a team of experienced compiler developers.
Skills
C++
LLVM
MLIR
ONNX
TensorFlow
PyTorch
Compiler Development
Algorithm Design
Torch-MLIR
ONNX-MLIR
Caffe
TVM
Model Partitioning
Tiling
Resource Allocation
Memory Management
Scheduling
Optimization
d-Matrix
AI compute platform for datacenters
About d-Matrix
d-Matrix focuses on improving the efficiency of AI computing for large datacenter customers. Its main product is the digital in-memory compute (DIMC) engine, which combines computing capabilities directly within programmable memory. This design helps reduce power consumption and enhances data processing speed while ensuring accuracy. d-Matrix differentiates itself from competitors by offering a modular and scalable approach, utilizing low-power chiplets that can be tailored for different applications. The company's goal is to provide high-performance, energy-efficient AI inference solutions to large-scale datacenter operators.
Key Metrics
Santa Clara, CaliforniaHeadquarters
2019Year Founded
$149.8MTotal Funding
SERIES_BCompany Stage
Enterprise Software, AI & Machine LearningIndustries
201-500Employees