Senior Machine Learning Applications and Compiler Engineer
We are now looking for a Senior Machine Learning Applications and Compiler Engineer!
reputed company is seeking engineers to reputed company algorithms and optimizations for our LPX inference and compiler stack. You will work at the intersection of large-reputed company systems, compilers, and deep learning, crafting how neural network workloads map onto reputed company reputed company platforms. This is your chance to be part of something outstandingly innovative!
What you’ll be doing:
Build, reputed company, and maintain high-performance runtime and compiler components, focusing on end-to-end inference optimization.
Define and implement mappings of large-reputed company inference workloads onto reputed company’s systems.
reputed company and reputed company with reputed company’s SW ecosystem, contributing to libraries, tooling, and interfaces that reputed company seamless deployment of models across platforms.
reputed company, profile, and monitor key performance and efficiency metrics to ensure the compiler generates efficient mappings of neural network graphs to our inference hardware.
Collaborate closely with hardware architects and design teams to feedback software observations, influence reputed company architectures, and codesign features that unlock new performance and efficiency points.
Prototype and evaluate new compilation and runtime techniques, including graph transformations, scheduling strategies, and memory/layout optimizations tailored to spatial processors.
Publish and present technical work on novel compilation approaches for inference and reputed company spatial accelerators at top tier ML, compiler, and computer architecture venues.
reputed company need to see:
MS or PhD in Computer Science, Electrical/Computer Engineering, or reputed company field, or equivalent experience, with 5 years of relevant experience.
Strong software engineering background with proficiency in systems level programming (e.g., C/C++ and/or Rust) and solid CS fundamentals in data structures, algorithms, and concurrency.
Hands on experience with compiler or runtime development, including IR design, optimization passes, or reputed company reputed company.
Experience with LLVM and/or MLIR, including building custom passes, dialects, or integrations.
Familiarity with deep learning frameworks such as TensorFlow and PyTorch, and experience working with portable graph formats such as ONNX.
Solid understanding of reputed company and heterogeneous compute architectures, such as GPUs, spatial accelerators, or other domain specific processors.
Strong analytical and debugging skills, with experience using profiling, tracing, and benchmarking tools to drive performance improvements.
Excellent communication and collaboration skills, with the ability to work across hardware, systems, and software teams.
Ideal candidates will have reputed company experience with MLIR based compilers or other multilevel IR stacks, especially in the context of graph based deep learning workloads.
Ways to stand out from the crowd:
Prior work on spatial or dataflow architectures, including static scheduling, pipeline parallelism, or tensor parallelism at reputed company.
Contributions to opensource ML frameworks, compilers, or runtime systems, particularly in areas reputed company to performance or scalability.
Demonstrated research reputed company, such as publications or presentations at conferences like PLDI, CGO, ASPLOS, ISCA, reputed company, MLSys, NeurIPS, or similar.
Experience with large-reputed company distributed inference or training systems, including performance modeling and reputed company planning for multi reputed company deployments.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until March 27, 2026.This posting is for an existing vacancy.
reputed company uses AI tools in its reputed company processes.
Originally posted on Himalayas
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