Senior Windows System Software Engineer (Kernel and Telemetry)

Luxoft; Gdańsk; On-site; PLN 180,000 - 300,000; Full time

Job summary

Luxoft in Poland seeks a Senior Windows Systems Engineer (Kernel & Telemetry) to design and optimize Windows runtime components that transfer CPU telemetry from kernel space to user space and tie it to the ML inference pipeline. This on-site role collaborates with hardware, ML, validation, and SDK/API teams.

You will implement low-latency pipelines, shared memory and IOCTL communication, and robust error handling while improving latency, throughput, and memory use.

Qualifications

• 4+ years of professional experience in systems programming using C or C++.
• Hands-on Windows kernel-mode development and kernel-to-user-space communication.
• Strong knowledge of concurrency, multithreading, synchronization, and memory management.
• Experience with low-latency, high-throughput software and production-grade systems.
• Good debugging, profiling, and troubleshooting skills.
• Ability to document software architecture and interfaces.

Responsibilities

• Design, develop, and maintain Windows components using C/C++ for telemetry transfer.
• Implement efficient kernel-to-user/space communication and low-latency pipelines.
• Integrate telemetry with ML inference runtime and ensure data flow integrity.
• Develop tests and diagnostics for runtime components and interfaces.
• Collaborate with hardware, ML, validation, and SDK/API teams on integration.

Skills

Windows kernel-mode development

C/C++

Concurrency & multithreading

Low-latency / high-throughput

Inter-process communication

Performance profiling

OO design / architecture

Education

University degree in CS/EE/CE

Tools

WDK

KMDF

UMDF

IOCTLs

WinDbg

ETW/ETL

Job description

DXC Luxoft is a global IT services and consulting company, part of DXC Technology, delivering cutting-edge digital and software solutions worldwide. We partner with leading financial institutions and global enterprises, helping them transform and scale through modern technology.

Join a global community of engineers and be part of building impactful, modern technology solutions!

Project Description:

AMD is developing a hardware-assisted security platform that uses silicon-level Performance Monitoring Counters (PMCs) and on-chip machine learning to detect advanced endpoint threats, including ransomware, fileless malware, and cryptojacking.

The platform collects CPU behavioral telemetry, processes it through an ML inference engine, and exposes threat signals to security-software partners through a standardized API.

The project spans CPU telemetry collection, ML integration, real-time processing, hardware validation, and partner integration.

We are looking for a Senior Windows Systems Engineer (Kernel & Telemetry) to develop and optimize the Windows runtime components responsible for transferring CPU telemetry from kernel space to user space and integrating it with the ML inference pipeline.

You will work closely with engineers specializing in hardware, machine learning, validation, and partner integration.

This is a Windows-focused role requiring regular on-site collaboration in Gdańsk. Additional technical details will be shared during the recruitment process in accordance with applicable confidentiality requirements.

Responsibilities:

• Design, develop, and maintain performance-sensitive Windows components using C/C++.
• Implement efficient communication between Windows kernel-mode components and user-space services.
• Develop and optimize low-latency pipelines for collecting, transferring, and processing CPU telemetry.
• Integrate the telemetry pipeline with an ML inference runtime, including data preparation, inference execution, and result handling.
• Implement reliable concurrency, synchronization, buffering, and error-recovery mechanisms.
• Support accurate attribution of telemetry and inference results to processes and threads.
• Investigate performance bottlenecks and optimize latency, throughput, CPU utilization, and memory consumption.
• Develop automated tests and diagnostics for runtime components and their interfaces.
• Collaborate with ML, Lab, and SDK/API engineers on end-to-end integration, troubleshooting, and validation.
• Document component architecture, interfaces, implementation decisions, and performance characteristics.

Mandatory Skills:

• 4+ years of professional experience in systems programming using C or C++.
• Hands-on experience with Windows kernel-mode development and kernel-to-user-space communication, including technologies such as WDK, KMDF, UMDF, IOCTLs, WinDbg, or ETW/ETL.
• Strong knowledge of concurrency, multithreading, synchronization, and memory management.
• Experience developing performance-sensitive, low-latency, or high-throughput software.
• Familiarity with mechanisms such as shared memory, ring buffers, asynchronous I/O, or equivalent communication techniques.
• Strong debugging, profiling, and troubleshooting skills.
• Experience developing and testing reliable production-oriented systems software.
• Ability to understand technical specifications and document software architecture and interfaces.
• University degree in computer science, electrical engineering, computer engineering, or an equivalent field.

Nice-to-Have Skills:

• Familiarity with x86-64 CPU performance monitoring, PMCs, PMUs, or processor telemetry.
• Experience integrating ML inference runtimes such as ONNX Runtime, OpenVINO, or DirectML.
• Experience with SDK/API development, interface versioning, or external software integration.
• Familiarity with endpoint security, EDR, anti-malware, or system monitoring solutions.
• Experience with hardware-in-the-loop testing or validation across different hardware configurations.
• Knowledge of GPU/NPU acceleration or AMD hardware technologies.
• Familiarity with Windows driver signing and certification processes.
• What Makes This Role Interesting
• Work close to the hardware on modern AMD processor platforms.
• Develop low-level Windows software where latency, throughput, and reliability matter.
• Connect CPU-level telemetry with machine learning inference.
• Contribute to an emerging approach to endpoint security based on hardware-assisted threat detection.
• Collaborate with specialists across systems programming, silicon telemetry, ML, and hardware validation.