Sr. Compiler Engineer

About the Role

As part of Anthriq's mission to democratize neurotechnology, we are seeking a Senior Compiler Engineer to lead the design of performance-critical, low-level system software that sits close to our hardware stack and powers real-time Brain–Computer Interface (BCI) applications.

This role is ideal for someone who has deep expertise in C++ systems programming, OS/kernel fundamentals, compiler/toolchain awareness, and hardware–software integration, and who thrives at the intersection of neuroscience, embedded systems, and scalable real-time computing.

You will architect, implement, and optimize the core system layer — from device drivers and real-time data pipelines to system services and API abstractions. You will work across:

• Compiler and toolchain optimization
• OS-level and kernel subsystems
• Real-time signal acquisition
• High-performance C++ runtimes
• Embedded and edge-level architectures

You will provide strong technical leadership, mentor engineering teams, and collaborate closely with hardware, firmware, algorithms, and AI researchers.

Responsibilities

System Architecture & OS-Level Design

• Architect modular, extensible system frameworks that interface directly with hardware and firmware
• Define low-level hardware/firmware/kernel/driver/API interfaces
• Make critical architectural decisions balancing latency, throughput, and reliability
• Drive compiler/toolchain optimization strategies for performance-critical paths

Core Low-Level Development

• Develop high-performance C++14/17/20 system components with a focus on:
  • Low-latency, real-time execution
  • Multi-threading, synchronization, lock-free structures
  • Memory management, allocation strategies, and cache efficiency
• Implement device drivers, communication protocols, real-time signal acquisition and streaming pipelines
• Build OS-level abstractions and libraries that expose hardware capabilities to higher-level SDKs

Hardware–Software & Kernel Integration

• Collaborate with hardware teams on embedded interfaces and sensor data pipelines
• Optimize software performance on Embedded Linux, RTOS environments, FPGAs and edge processors
• Work with kernel subsystems, interrupts, I/O scheduling, and low-level performance tuning

Performance, Profiling & Reliability

• Profile and optimize systems across CPU/GPU/accelerator architectures
• Use tools such as gdb, perf, valgrind, ltrace/strace, eBPF
• Implement production-grade reliability, fault-tolerance, recovery, and watchdog mechanisms

Leadership & Mentorship

• Define engineering standards, best practices, and system-level design docs
• Mentor engineers in C++, systems programming, compiler-level thinking, and performance engineering

Research & Innovation Alignment

• Stay current with cutting-edge work in OS internals, real-time computing, compiler optimizations (LLVM, Clang, GCC), and high-performance systems programming
• Translate algorithmic and neural-signal research into efficient runtime implementations

Requirements

Education: Master's in Computer Science/Engineering or related field. Exceptional Bachelor's candidates may be considered.

Experience: 9+ years in system-level C++ development, including OS-level, kernel, or compiler-adjacent work. Proven track record building complex, production-grade low-level systems.

Core Technical Skills:

• Expert C++ (C++14/17/20): STL, templates, design patterns, metaprogramming
• Multi-threading, concurrency, lock-free design and synchronization
• Memory models, allocators, and performance tuning
• Linux Kernel development, device drivers, system calls, interrupts
• Embedded Linux or RTOS
• Firmware interfaces, hardware bring-up
• Toolchains and compilers (LLVM, Clang, GCC)
• Debugging and profiling (gdb, perf, valgrind, sanitizers)
• Streaming, real-time signal processing, or high-frequency data acquisition

Bonus / Good to Have

• GPU programming (CUDA, OpenCL, Vulkan compute)
• Rust or Python integration with C++ pipelines
• Experience in neurotech, robotics, IoT, or any real-time hardware domain
• Knowledge of DSP, numerical methods, or ML-based signal processing