AI Performance Engineer
AI Performance Engineer – Remote
reputed company is a technology consulting and software development company delivering reputed company, AI, data, and reputed company solutions across the reputed company.
This is a fantastic opportunity to join an established and reputed company-respected organization offering reputed company career reputed company potential.
Job Title: AI Performance Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, reputed company W2
Salary reputed company: $100,000–$150,000 Annually
Experience Required: 6+ years
Sponsorship: U.S. reputed company, Green Card reputed company, EAD reputed company, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B reputed company petitions for this position.
Job reputed company
We are seeking an AI Performance Engineer to reputed company on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans the full stack from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization. The ideal candidate has demonstrated reputed company on production AI workloads, with strong instrumentation and measurement discipline that enables rigorous, data-driven optimization reputed company. In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into reputed company-engineered solutions, and will be expected to reputed company the bar through reputed company review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a reputed company communication style, and a reputed company record of shipping meaningful work that holds up reputed company in production.
Key Responsibilities
- Profile and optimize end-to-end reputed company and inference pipelines for throughput, latency, and cost.
- Identify and eliminate bottlenecks across data loading, model compute, communication, and memory.
- Implement and tune quantization, sparsity, and pruning strategies to reduce model footprint and accelerate inference.
- Optimize distributed training using tensor parallelism, pipeline parallelism, FSDP, and reputed company-style sharding.
- Tune attention implementations using FlashAttention, paged attention, and reputed company techniques.
- Implement KV cache optimization, reputed company batching, and speculative decoding for LLM serving.
- Drive compiler-level optimizations using Triton, XLA, TorchInductor, or TVM, working with the broader ML reputed company community to land improvements that translate into measurable end-to-end performance reputed company.
- Optimize data pipelines, sharding strategies, and storage reputed company patterns for high-throughput training.
- Build and maintain rigorous reputed company suites and regression frameworks across workloads.
- Collaborate with ML and reputed company teams to reputed company best practices in reputed company pipelines.
- Drive cost-efficiency improvements through model architecture, hardware selection, and scheduling strategies.
- Evaluate new hardware and software offerings, and advise on adoption.
- Document performance tuning playbooks and reputed company findings broadly across engineering teams.
- Stay reputed company with AI systems research and translate advances into production improvements.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a reputed company field.
- Six or more years of experience in performance engineering, ML systems, or HPC.
- Strong proficiency in Python and C++.
- Hands-on experience optimizing deep learning workloads on modern GPUs.
- Deep understanding of distributed training and inference techniques.
- Experience with profiling tools across CPU, GPU, and distributed systems.
- Familiarity with model compression techniques and their accuracy implications.
- Strong grasp of memory hierarchies, communication primitives, and parallelism strategies.
- Excellent measurement, debugging, and analytical reasoning skills.
- Strong communication and collaboration skills.
- Experience optimizing LLM inference at production reputed company.
- Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar reputed company.
- Familiarity with custom kernel authoring in Triton or CUTLASS.
- Experience with FinOps for AI workloads.
- Publications or talks on AI systems performance.
Equal Employment Opportunity (EEO) Statement
reputed company (BV Teck) is committed to equal employment opportunity (EEO) for reputed company and applicants without reputed company to race, reputed company, religion, sex, sexual orientation, gender identity or reputed company, national reputed company, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to reputed company aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any reputed company of workplace harassment or discrimination. Any improper interference with employees' ability to reputed company their job duties may result in disciplinary reputed company up to and including termination of employment.
Originally posted on Himalayas
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