Senior Software Engineer

AI Workload & Stress Tool Development Design and develop scalable stress, performance, and validation frameworks for MAIA AI accelerator platforms.

Build workload generation infrastructure capable of exercising compute, memory, interconnect, networking, storage, and system-level resources.

Develop reusable stress tools using PyTorch, Triton, Python, C++, and custom MAIA SDKs.

Create synthetic and production-inspired workloads that model training and inference behaviors observed in large-scale AI deployments.

Build automated infrastructure for workload deployment, orchestration, telemetry collection, and result analysis.

Develop and optimize kernels targeting custom AI accelerators.

Analyze execution behavior across the hardware-software stack and identify bottlenecks impacting utilization and performance.

Collaborate with compiler and runtime teams to improve workload efficiency and hardware utilization.

Develop tooling that integrates with MAIA compiler pipelines, SDKs, runtime environments, and performance analysis tools.

Build automation around model compilation, kernel validation, regression testing, and workload portability.

Design workload suites for platform bring-up, qualification, and reliability testing.

Build comprehensive regression infrastructure supporting silicon, firmware, system software, and platform releases.

Develop automated validation tools capable of identifying correctness, performance, thermal, power, and stability issues.

Enable platform readiness through scalable validation methodologies and continuous regression testing.

Develop benchmarking methodologies and performance dashboards.

Developer Productivity & Automation Improve developer productivity through automation, CI/CD integration, diagnostics, and debugging infrastructure.

Build reusable tooling for workload generation, failure triage, telemetry analysis, and reporting.

Develop dashboards and automated workflows for large-scale validation environments.

Software Engineering BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience. 8+ years of software development experience.

Strong programming skills in: Python C/C++ Experience designing production-quality software systems and frameworks.

developing workloads for GPUs, AI accelerators, or HPC systems.

Deep understanding of AI training and inference workloads.

Hands-on experience with: PyTorch Triton Distributed AI workloads Experience developing or optimizing compute-intensive kernels.

Understanding of modern accelerator architectures, including: Compute engines Memory hierarchy Interconnects Runtime systems Experience with performance profiling, bottleneck analysis, and workload optimization.

Familiarity with distributed systems and large-scale AI infrastructure.

developing stress, benchmark, validation, or reliability workloads.

building automated test frameworks and regression infrastructure.

working with custom AI accelerator SDKs and compiler ecosystems.

Familiarity with compiler technologies such as: LLVM, MLIR & Triton Compiler Experience with kernel generation frameworks and code generation pipelines.

with LLM training, inference, and AI model optimization.

Understanding of collective communication libraries and networking technologies.

with performance characterization of large-scale AI clusters.

Familiarity with CI/CD systems, containerized environments, and cloud-scale validation infrastructure.

working with silicon bring-up or post-silicon validation teams.