Company: Vicharak Computers Pvt. Ltd. Role: Compiler Engineer - Systems Engineer
Domain: AI Accelerators / Compilers / Systems Software
Location: Surat, Gujarat, India

About the Role

We are looking for a strong Systems Software Engineer to work on the compiler and runtime stack for our AI accelerator architecture.

This is a low-level engineering role for someone who enjoys working close to hardware and has strong fundamentals in C/C++, compilers, computer architecture, operating systems, and performance optimization .

The engineer will work closely with ASIC architecture and hardware teams to translate neural-network workloads into highly optimized execution on Vicharak's accelerator.

What You Will Work On
Design and develop the compiler stack for AI accelerator .
Build compiler passes for mapping AI workloads onto custom compute engines.
Develop graph-level and operator-level optimizations for neural-network workloads.
Implement kernel generation, scheduling, memory allocation, and data movement strategies.
Develop low-level runtime components and hardware abstraction layers.
Work on instruction generation and execution scheduling for the accelerator.
Optimize workloads for:
Matrix multiplication

GEMM

Convolution
Attention
Transformer workloads
Other AI/ML operators
Work closely with ASIC architects to understand:
Compute architecture
Memory hierarchy
On-chip memory
Dataflow
Instruction set / command architecture
DMA and memory movement
Profile workloads and identify performance bottlenecks.
Optimize for latency, throughput, memory bandwidth, and power efficiency.
Build debugging, profiling, benchmarking, and validation tools for the compiler stack.




Contribute to model deployment flows from popular AI frameworks to Vicharak hardware.

Required SkillsStrong C/C++ Programming
Candidates should have excellent proficiency in:
C
Modern C++
Data structures and algorithms
Memory management
Multithreading and concurrency
Low-level systems programming
Performance-oriented programming
The ability to understand generated assembly, memory layouts, cache behavior, and hardware/software interactions is highly desirable.

Systems Software Background
We are particularly interested in engineers who have previously worked on areas such as:
Compilers
Operating systems
Device drivers
GPU/NPU software stacks
Embedded systems
Runtime systems
High-performance computing
Databases/storage engines
Virtual machines
Networking stacks
Firmware
Hardware acceleration
A solid systems software portfolio is more important to us than experience with any single AI framework.

Preferred Compiler Experience
Experience with one or more of the following is highly valuable:

LLVM

MLIR

TVM

OpenXLA / XLA
Triton
GCC internals
Custom compiler development
Intermediate representations
Compiler optimization passes
Code generation
Instruction scheduling
Register allocation
Tensor compilers
Candidates without direct AI compiler experience may still be considered if they have exceptional systems programming and compiler fundamentals.

AI / Hardware Knowledge




Understanding of the following is preferred:
Neural-network inference
Transformers
GEMM and matrix multiplication
Quantization
Floating-point and low-precision numerical formats
SIMD / vector architectures
GPUs, NPUs, TPUs, or AI accelerators
Memory hierarchy and bandwidth
SRAM / DRAM / cache architectures

DMA

Parallel computing
Computer architecture

What We Value
We are looking for engineers who can think from both the software and hardware perspective .
You should be comfortable asking questions such as:
How should this neural-network graph be mapped onto the hardware
How should tensors be partitioned across compute units
Where should intermediate data reside
How can we minimize memory movement
How should instructions be scheduled to maximize utilization
How can compiler decisions improve tokens/watt and overall throughput
What architectural changes would make the compiler significantly more efficient

Portfolio Expectations
Candidates should ideally be able to demonstrate previous systems-level work through one or more of:
GitHub projects
Open-source contributions
Compiler projects
Operating-system projects
Embedded software
Runtime systems
GPU/NPU programming
Performance optimization projects
Research projects
Production systems software
We strongly value candidates who have built substantial low-level systems software themselves .

Why Join Vicharak
At Vicharak, this role is not about maintaining an existing compiler.
You will have the opportunity to help define the software architecture for a new AI accelerator from the ground up , working directly with the engineers designing the underlying silicon.

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