AI Systems Performance Specialist

We need to output only HTML fragment, using

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. No job title heading. No Job ID etc. Remove boilerplate, navigation, EEO, etc. Also remove application instructions (Apply today...). Also remove contact info? The instructions: "Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions." So we should remove the "Interested in this opportunity? Apply today..." lines, email, phone, website, EEO statement, etc. Also remove "Powered by JazzHR aygtziHWiY". Also remove "Job Title AI Systems Performance Specialist Location: 100% Remote (Continental United States) Position Type: Full-time, Direct W2 Salary Range: $130,000–$180,000 Annually Experience Required: 10+ Years Sponsorship: ..." This is metadata; we can fold minor metadata into a short

or drop it. The instruction: "do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we can include a short paragraph summarizing location, type, salary, sponsorship maybe. But we need to preserve all substantive information. The substantive info includes location (100% Remote Continental US), position type (Full-time, Direct W2), salary range ($130k-180k), experience required (10+ years), sponsorship (US Citizens, Green Card Holders, EAD Holders, H-1B transfer candidates encouraged; unable to sponsor new H-1B). Also the company description at start: "Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential." That's substantive. Also the Job Summary paragraph. Also Key Responsibilities list. Also Required Qualifications list. Also Preferred Qualifications list. Also maybe Skills? The posting includes many skills within responsibilities and qualifications. We could create a Skills section if there is explicit list of skills; but we can also embed them in Responsibilities/Qualifications. The instruction: "Prefer a few substantive sections over many thin ones." So we might combine some. We need headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We should include only those with real content. - About the role: could include company description and job summary. That's substantive. - Responsibilities: we have Key Responsibilities list. - Requirements: maybe combine experience required, education, etc. Could be "Requirements" heading for required qualifications. - Qualifications: maybe separate "Required Qualifications" and "Preferred Qualifications"? But we only have one Qualifications heading allowed; we could put both required and preferred under Qualifications, maybe split with subheadings? But we cannot add extra headings beyond those listed? The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but says "Use

for section headings (e.g. ...)". Likely we should stick to those headings. We could have Required Qualifications under Requirements heading, and Preferred Qualifications under Qualifications heading? Or we could have Requirements for required, Qualifications for preferred. Or we could combine both under Qualifications and omit Requirements. But we need to preserve all substantive info. Let's think: The posting has "Required Qualifications" and "Preferred Qualifications". We could map Required Qualifications to "Requirements" heading, and Preferred Qualifications to "Qualifications" heading. That seems logical. - Skills: Could we extract a list of skills? The posting includes many skills like GPU optimization, distributed training, etc. But they are already in responsibilities and qualifications. Might be thin to create a separate Skills section. Better to omit Skills if no explicit list. - Benefits: Not mentioned. No benefits details. So omit Benefits. - Pay: Salary range is given. So we can include Pay section with that info. - Schedule: Position type full-time, remote. Could include Schedule section with "Full-time, Remote (Continental United States)". Or we could include location and type under About the role. But we have Schedule heading available; we could put schedule info there. However we also need to preserve location and sponsorship etc. Could put location, type, sponsorship under About the role or a short paragraph. The instruction: "fold minor metadata into a short

or drop it." So we could include a short paragraph after About the role maybe containing location, employment type, salary, sponsorship. But we also have Pay and Schedule headings for salary and schedule. So we could put salary in Pay, schedule in Schedule, and location/sponsorship maybe in About the role or a separate short paragraph. Let's structure:

About the role

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Location: 100% Remote (Continental United States)

Position Type: Full-time, Direct W2

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. Unable to sponsor new H-1B visa petitions.

But we need to avoid using strong? Not prohibited. Could just be plain text. Then

Responsibilities

with

• each responsibility. Then

  Requirements

  for Required Qualifications (education, experience, skills). Could be a
  . Then

  Qualifications

  for Preferred Qualifications. Then

  Pay

  with salary range. Then

  Schedule

  with Full-time, Remote (Continental United States) maybe. But we already included location and type in About the role; maybe we should not duplicate. However we need to preserve all substantive info; duplication is okay? The instruction says remove duplicated lines. So we should avoid duplicating same info. So we should not repeat location/type in both About and Schedule. We could put location and type in Schedule, and keep About role just company description and job summary. Sponsorship maybe also in About role or separate short paragraph. Let's think. Better: About the role: company description and job summary. Then Schedule: Full-time, Remote (Continental United States). Pay: salary range. Sponsorship maybe could be included in About role or a separate short paragraph under About role? But we could add a short paragraph under About role for sponsorship. However we already have About role with company description and job summary; we can add another paragraph for sponsorship. That's fine. Thus:

  About the role

  Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

  Job Summary: Bright Vision Technologies is seeking a highly experienced AI Systems Performance Specialist with 10+ years of experience in AI infrastructure, machine learning systems, High-Performance Computing (HPC), and performance engineering. The ideal candidate will optimize AI training and inference workloads for maximum performance, scalability, reliability, and cost efficiency. This role requires deep expertise in GPU optimization, distributed training, Large Language Model (LLM) inference, Python, C++, CUDA, and production AI systems, along with the ability to lead performance optimization initiatives across enterprise-scale AI platforms.

  Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. Unable to sponsor new H-1B visa petitions.

  Then

  Responsibilities

  with list. Then

  Requirements

  for Required Qualifications. Then

  Qualifications

  for Preferred Qualifications. Then

  Pay

  with salary range. Then

  Schedule

  with Full-time, Remote (Continental United States). We should not include Benefits. Now ensure we don't include any boilerplate like EEO, application instructions, etc. Check that we preserved all substantive info: company description, job summary, responsibilities list, required qualifications list, preferred qualifications list, salary range, location, position type, sponsorship. Also we included job summary details. Did we include the "Experience Required: 10+ Years"? That's covered in Required Qualifications (we will list 10+ years experience). Also we included "Bachelor's or Master's degree..." etc. Now format. We need to output only HTML fragment, no markdown fences. Let's craft. Responsibilities list items: copy each bullet from Key Responsibilities. List: - Optimize AI training and inference pipelines for maximum throughput, low latency, scalability, and infrastructure efficiency - Analyze and improve GPU utilization, memory management, kernel execution, and multi-GPU performance across production AI workloads - Design and implement optimization techniques including quantization, pruning, mixed precision, batching, caching, speculative decoding, and model parallelism - Profile AI applications using industry-standard performance analysis tools and identify bottlenecks across compute, memory, networking, and storage - Optimize distributed training and inference using NCCL, DeepSpeed, PyTorch Distributed, Ray, MPI, or similar distributed computing frameworks - Collaborate with AI researchers, ML engineers, platform engineers, and infrastructure teams to improve model performance and production reliability - Build automated benchmarking frameworks, performance dashboards, monitoring solutions, and regression testing pipelines - Evaluate emerging AI hardware, GPU architectures, inference frameworks, and optimization technologies to improve enterprise AI capabilities - Drive AI infrastructure cost optimization through efficient resource utilization, cloud optimization, and FinOps best practices - Mentor engineering teams and provide technical leadership on AI systems architecture, GPU optimization, and performance engineering Now Required Qualifications list: - Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, or a related technical discipline - 10+ years of professional experience in performance engineering, AI infrastructure, machine learning systems, High-Performance Computing (HPC), or distributed computing - Expert-level programming skills in Python and C++ - Extensive experience optimizing GPU-accelerated AI workloads using CUDA, distributed training frameworks, and modern deep learning libraries - Strong knowledge of Large Language Models (LLMs), deep learning frameworks, model serving, and production AI inference - Hands-on experience with profiling tools such as NVIDIA Nsight Systems, Nsight Compute, PyTorch Profiler, TensorBoard, or similar performance analysis tools - Experience deploying and optimizing AI workloads on AWS, Microsoft Azure, or Google Cloud Platform (GCP) - Strong understanding of distributed systems, networking, storage optimization, and AI infrastructure architecture - Excellent analytical, troubleshooting, communication, and technical leadership skills Preferred Qualifications list: - Experience optimizing production-scale LLM inference and serving large foundation models - Hands-on experience with vLLM, TensorRT-LLM, DeepSpeed, Triton Inference Server, CUTLASS, FasterTransformer, or similar AI optimization frameworks - Knowledge of model compression, KV cache optimization, speculative decoding, and advanced inference optimization techniques - Experience implementing FinOps strategies for AI infrastructure cost optimization and resource management - Contributions to AI systems research, open-source AI infrastructure projects, patents, or technical publications - Familiarity with emerging AI accelerator technologies, including AMD ROCm, Intel oneAPI, or custom AI hardware Now Pay: Salary Range: $130,000–$180