Compiler Engineer

Evollabs Tech; Bengaluru; On-site; INR 2,500,000 - 5,500,000; Full time

Job summary

Evollabs Tech in Bengaluru is seeking an experienced Senior Compiler Engineer to design and implement MLIR dialects and lowering pipelines for our AI accelerator/NPU platform. You will translate high‑level ML graphs into optimized kernels, aiming for low latency and high throughput while balancing power requirements.

You will collaborate with silicon, firmware, runtime, datacenter software and architecture teams to shape the compiler stack, co‑design features, and drive multi‑die scheduling.

Qualifications

• Minimum 5+ years of experience in compiler engineering or high‑performance systems.
• Strong programming skills in C++ (modern standards), and scripting or tooling in Python.
• Hands‑on experience with MLIR and/or LLVM (designing/extending dialects, lowering, optimization).
• Deep understanding of compiler internals: IRs, code scheduling, vectorization, loop transformations.
• Strong familiarity with AI/ML frameworks (e.g., PyTorch, ONNX, TensorFlow).
• Excellent understanding of ML ops such as tensor operators, matmuls, quantization, dynamic shapes.
• Robust understanding of computer architecture and memory hierarchy.
• Bachelor's (or higher) degree in Computer Science, Computer Engineering or equivalent.

Responsibilities

• Define and implement MLIR dialects and lowering pipelines targeting our AI‑accelerator/NPU platform.
• Lower ML graphs (e.g., from ONNX/PyTorch) into optimized kernels focusing on fusion, tiling and vectorization.
• Profile, benchmark and optimize compiler output to meet latency, throughput and power targets.
• Work with hardware architects and runtime/framework teams to co‑design compiler features.
• Build a future‑ready, portable compiler stack that supports multiple hardware generations.
• Lead and mentor junior engineers within the compiler team.

Skills

C++

Python

MLIR/LLVM

Compiler internals

AI/ML frameworks

Computer architecture

Education

Bachelor's degree in Computer Science or Computer Engineering

Tools

MLIR

LLVM

C++ tooling

Job description

About Us

We are a tech company specializing in the design and development of cutting-edge, customized server hardware solutions optimized for artificial intelligence and machine learning applications. Our mission is to empower businesses and researchers to accelerate their AI initiatives by providing them with high-performance, scalable, and energy-efficient hardware infrastructure.

About Us

We are a tech company specializing in the design and development of cutting-edge, customized server hardware solutions optimized for artificial intelligence and machine learning applications. Our mission is to empower businesses and researchers to accelerate their AI initiatives by providing them with high-performance, scalable, and energy-efficient hardware infrastructure.

As a rapidly growing company at the forefront of AI hardware innovation, we are constantly seeking talented and motivated individuals to join our team. We offer a dynamic and challenging work environment, with opportunities to make a significant impact on the future of AI technology.

You’ll Collaborate With

Silicon, firmware, runtime, datacenter-software and architecture teams to build a mlir-compiler and software stack that brings next-gen AI/NPU hardware into modern datacenter environments and production AI workloads.

What You’ll Own

• Define and implement MLIR dialects and lowering pipelines targeting our AI-accelerator/NPU platform.
• Lower ML graphs (e.g., from ONNX/PyTorch) into optimized kernels focusing on fusion, tiling and vectorization.
• Profile, benchmark and optimize compiler output to meet latency, throughput and power targets.
• Work with hardware architects and runtime/framework teams to co-design compiler features.
• Build a future‑ready, portable compiler stack that supports multiple hardware generations.

Minimum Qualifications

• 5+ years of experience in compiler engineering or high‑performance systems.
• Strong programming skills in C++ (modern standards), and scripting or tooling in Python.
• Hands‑on experience with MLIR and/or LLVM (designing/extending dialects, lowering, optimization).
• Deep understanding of compiler internals: IRs, code scheduling, vectorization, loop transformations.
• Strong familiarity with AI/ML frameworks (e.g.,PyTorch, ONNX, TensorFlow).
• Excellent understanding of ML operations such as tensor operators, matmuls, quantization, dynamic shapes.
• Robust understanding of computer architecture and memory hierarchy.
• Bachelor's (or higher) degree in Computer Science, Computer Engineering or equivalent.

Preferred Qualifications

• Prior experience targeting NPU/AI accelerator hardware.
• Contributions to open‑source compiler projects (MLIR, LLVM,Torch-MLIR, ONNX-MLIR).
• Familiarity with runtime systems, scheduling, resource sharing, memory movement engines and, interconnects.
• Previous leadership role driving compiler architecture, setting standards, mentoring teams and owning roadmap.
• Familiarity with software development tooling: Git, CI/CD, debuggers, profilers.
• Advanced degree (M.S./Ph.D.) preferred.

What Success Looks Like (First 6–9 Months)

• A production compiler IR/dialect is designed and integrated, successfully lowering key ML workloads to the target NPU.
• Key operator kernels (matmul, convolution, etc) show measurable performance gains (reduced latency, increased throughput) on the hardware or simulator.
• The compiler pipeline handles multi‑die/chiplet topology correctly and efficiently schedules across devices.
• Runtime interfaces and resource scheduling between host and accelerator are functional and validated with real workloads.
• Telemetry/debug hooks and performance counters from compiled code are available and used for performance analysis by other teams.
• The architecture and roadmap for next‑gen hardware are defined, and junior engineers are actively mentored within the compiler team.

Join us in our mission to democratize AI compute — where your firmware expertise becomes the bedrock of tomorrow's AI breakthroughs.