Linux Kernel Engineer

Evollabs; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Evollabs in Hyderabad, India is seeking an experienced Linux kernel driver engineer to design and optimize PCIe-based accelerator drivers for AI workloads. You will work across firmware, kernel, and datacenter teams to deliver reliable, high-throughput systems with strong observability and multi-die orchestration capabilities.

The role emphasizes low-latency DMA, robust error handling, and deep hardware understanding, with opportunities to contribute upstream and influence platform reliability

Qualifications

• 5+ years developing Linux kernel drivers and subsystems in C for complex SoCs or accelerators.
• Proven experience with PCIe device driver development (enumeration, BARs, DMA, interrupts).
• Strong knowledge of Linux memory management, DMA mapping, and IOMMU integration.
• Hands-on experience with kernel synchronization primitives, workqueues, and interrupt handling.
• Solid understanding of Linux device model, sysfs/debugfs, and driver lifecycle management.
• Familiarity with kernel debugging tools: ftrace, perf, crash, kprobes, and hardware debuggers.
• Ability to read hardware specifications and work with RTL/hardware teams on register interfaces.
• Excellent documentation habits; comfortable with kernel development processes and upstream contribution.

Responsibilities

• PCIe Foundation: Design and implement robust PCIe kernel drivers for AI accelerator enumeration, configuration, and management.
• High-Speed Data Movement: Develop DMA engines and memory management systems for zero-copy data transfer.
• Firmware Bridge: Build interrupt handling and mailbox communication protocols between kernel space and firmware.
• System Observability: Create sysfs/debugfs interfaces for device configuration, telemetry, and diagnostics.
• Multi-Die Orchestration: Support multi-die topologies through device discovery, link management, and topology coordination.
• Power & Thermal Intelligence: Develop power management and thermal control integration with Linux PM frameworks.
• Reliability Engineering: Contribute to device health monitoring, error handling (RAS), and recovery mechanisms.
• Performance Optimization: Optimize kernel-space performance for AI workloads with latency and throughput focus.
• Time Synchronization: Support PTP/PHC time synchronization for distributed training and inference.
• Runtime Partnership: Collaborate with userspace runtime teams on kernel-userpace interfaces and APIs.
• Future-Ready Architecture: Lay groundwork for device virtualization and multi-tenant isolation.

Skills

Linux kernel drivers

PCIe driver development

Linux memory management

DMA mapping

Kernel synchronization

Sysfs/debugfs

Device model lifecycle

Kernel debugging tools

RTL hardware interfacing

Tools

Ftrace

Perf

Crash

Kprobes

Job description

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

Firmware, silicon, runtime, datacenter software and architects teams to deliver a robust kernel foundation that integrates seamlessly with modern datacenter environments and AI workloads.

What You’ll Own

• PCIe Foundation: Design and implement robust PCIe kernel drivers for AI accelerator enumeration, configuration, and management that form the critical host-device communication backbone.
• High-Speed Data Movement: Develop DMA engines and memory management systems that deliver zero-copy, high-throughput data movement between host and accelerator for massive AI workloads.
• Firmware Bridge: Build interrupt handling (MSI/MSI-X) and mailbox communication protocols that create seamless coordination between kernel space and our firmware stack.
• System Observability: Create comprehensive sysfs/debugfs interfaces for device configuration, telemetry, and diagnostics that give operators deep visibility into accelerator operations.
• Multi-Die Orchestration: Support multi-die topologies through device discovery, link management, and topology coordination that scales from single-card to cluster deployments.
• Power & Thermal Intelligence: Develop power management and thermal control integration with Linux PM frameworks that optimize performance while maintaining reliability.
• Reliability Engineering: Contribute to device health monitoring, error handling (RAS), and recovery mechanisms that deliver the 99.99% uptime datacenter customers require.
• Performance Optimization: Optimize kernel-space performance for AI workloads, focusing on latency, throughput, and scalability that directly impacts model training and inference speed.
• Time Synchronization: Support PTP/PHC time synchronization for distributed training and inference that ensures coordination across multi-node AI clusters.
• Runtime Partnership: Collaborate with userspace runtime teams on kernel-userspace interfaces and APIs that enable efficient scheduling and resource sharing.
• Future-Ready Architecture: Lay the groundwork for device virtualization and multi-tenant isolation, ensuring our platform can evolve with customer needs.

Minimum Qualifications

• 5+ years developing Linux kernel drivers and subsystems in C for complex SoCs or accelerators
• Proven experience with PCIe device driver development (enumeration, BARs, DMA, interrupts)
• Strong knowledge of Linux memory management, DMA mapping, and IOMMU integration
• Hands-on experience with kernel synchronization primitives, workqueues, and interrupt handling
• Solid understanding of Linux device model, sysfs/debugfs, and driver lifecycle management
• Familiarity with kernel debugging tools: ftrace, perf, crash, kprobes, and hardware debuggers
• Ability to read hardware specifications and work with RTL/hardware teams on register interfaces
• Excellent documentation habits; comfortable with kernel development processes and upstream contribution

Preferred Qualifications

• Experience with AI/ML accelerator drivers or GPU compute drivers (NVIDIA, AMD, Intel)
• Implemented RDMA/RoCE drivers or high-speed networking kernel subsystems
• Background in PTP/PHC time synchronization or distributed system timing
• Multi-die/chiplet device driver experience and topology management
• Linux kernel upstream contributions and familiarity with kernel community processes
• Experience with kernel security features, SELinux integration, and device isolation
• Knowledge of container/runtime integration with kernel drivers (Docker, Kubernetes)
• Performance optimization experience for high-throughput, low-latency kernel subsystems
• Familiarity with RAS concepts, ECC handling, and system reliability in kernel space

What Success Looks Like (First 6–9 Months)

• PCIe driver is stable and reliable across multiple system configurations and stress tests
• DMA and memory management achieve target throughput with low CPU overhead
• Multi-die topology management and inter-card communication is functional and performant
• Integration with firmware mailbox protocols and telemetry collection is operational
• Performance benchmarks meet targets for key AI workloads (inference and training)
• Documentation and test coverage enable team-wide development and deployment

Ready to accelerate the future of AI from the firmware up?

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