#1 AI DIGITAL Logistics TMS - maximum customer experience artificial intelligence freight matching-global visibility
Senior/Principal Performance Engineer
Location
United States
Posted
29 days ago
Salary
0
Seniority
Senior
Job Description
Senior/Principal Performance Engineer
TMSfirst
• Design, develop, and maintain comprehensive benchmarking frameworks spanning OS, kernel, and application layers. • Profile workloads across CPU, memory, I/O, network, and accelerator (GPU/NPU) subsystems to identify bottlenecks and optimization opportunities. • Establish and own performance baselines across CIQ's product and solutions portfolio. • Leverage AI-assisted tooling and agentic workflows to accelerate profiling, analysis, and root cause identification. • Build and maintain automated performance regression-detection pipelines integrated into CI/CD workflows using Fuzzball. • Identify, triage, and resolve regressions across user space, kernel space, and application layers with urgency and rigor. • Collaborate across engineering teams to root-cause regressions introduced by upstream kernel changes, compiler updates, or library modifications. • Drive proactive performance improvements - not just reactive fixes - to keep CIQ solutions ahead of the competition across every layer of the stack. • Own core operating system performance: kernel subsystem tuning (scheduler, memory management, I/O, networking), system call overhead reduction, and user space library and runtime optimizations. • Identify and implement kernel-level enhancements, including patches, configuration changes, and upstream contributions that yield measurable performance gains for CIQ's customer workloads. • Optimize for AI inference and training workloads, including LLM serving, model parallelism, and accelerator utilization. • Tune performance for HPC workloads, including modeling, simulation, and tightly coupled parallel applications (MPI, OpenMP, etc.). • Optimize general computing and service workloads - web services, databases, messaging systems, and other production software that runs on CIQ's OS platform. • Work at all levels of the stack: compiler flags, kernel parameters, scheduler tuning, NUMA topology, memory allocation, and application-level algorithmic improvements. • Champion an AI-first engineering philosophy - use AI tools, agents, and automation to accelerate your own productivity and the quality of performance insights. • Identify and prioritize optimization opportunities that directly impact AI training throughput and inference latency/cost. • Stay current on state-of-the-art techniques in ML system performance, including quantization, batching strategies, kernel fusion, and hardware-software co-design. • Develop deep expertise in CIQ's Fuzzball platform - its architecture, scheduling, and workload execution model. • Integrate performance benchmarks, regression tests, and user-facing workloads into Fuzzball-based pipelines. • Contribute to the performance characterization of Fuzzball itself, ensuring the platform adds minimal overhead and scales efficiently. • Develop broad familiarity with the full CIQ product portfolio — including Rocky Linux and RLC (and its variants), Fuzzball, Apptainer (formerly Singularity), and Warewulf - understanding how performance considerations span and interconnect across each. • Collaborate deeply with the engineering teams behind each product line to surface, prioritize, and deliver performance improvements that benefit customers across the entire CIQ ecosystem. • Partner with product and customer success teams to translate real-world performance pain points into engineering priorities and measurable outcomes. • Document and communicate findings clearly - from low-level profiling data to executive-level summaries. • Contribute to technical publications, conference presentations, and thought leadership that reinforces CIQ's reputation for performance excellence.
Job Requirements
- A deep, principled understanding of operating system internals - Linux kernel scheduler, memory subsystem, I/O stack, and networking.
- Proven experience identifying and resolving performance regressions across kernel and user space in production environments.
- Hands-on expertise with profiling and tracing tools: perf, eBPF/bpftrace, Flamegraphs, VTune, Nsight, strace, ftrace, and similar.
- Strong background in AI/ML workload performance - including inference optimization (TensorRT, ONNX, vLLM, or similar), training efficiency, and GPU/accelerator utilization.
- Experience with HPC workloads: MPI, OpenMP, parallel filesystems, RDMA/InfiniBand, and job schedulers (Slurm, PBS, etc.).
- Familiarity with modern AI-first development workflows and comfort using LLM-based tools to accelerate engineering work.
- Experience building automated performance testing and regression detection pipelines in CI/CD environments.
- Excellent analytical skills - able to form hypotheses, design experiments, and draw actionable conclusions from complex data.
- Strong written and verbal communication skills; able to present findings to both deeply technical audiences and business stakeholders.
- A collaborative, humble, and always-learning mindset - combined with the confidence to champion performance as a first-class engineering concern.
Benefits
- Medical, dental, and vision insurance.
- Flexible paid time off.
- Employee stock options.
- Remote work; no travel required for most positions.
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