Remote AI Inference Performance Engineer

positron.ai; EUA; Teletrabalho; USD 160 000 - 260 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical coverage

Dental coverage

Vision coverage

Life insurance

Disability insurance

Equity

401(k) match

Unlimited PTO

13 paid holidays

Resumo da oferta

positron.ai is seeking an experienced engineer to improve end-to-end performance for large language model inference on custom accelerator systems. You will work across attention, data movement, and serving layers to optimize latency and throughput.

You will profile using counters and traces, develop distributed inference features including KV-cache management, and build benchmarks to expose limits. The role is remote-first in the United States with equity and comprehensive benefits.

Qualificações

• Strong C++ and Python skills with Linux systems profiling and optimization.
• Experience profiling and optimizing complex Linux systems that use VFIO interfaces.
• Hands-on profiling experience; tools and further qualifications not listed in the ad.

Responsabilidades

• Profile and optimize latency, throughput, utilization, and efficiency across accelerator, runtime, host, and on-device execution.
• Use performance counters, traces, telemetry, and simulation to isolate regressions and assess fixes.
• Develop distributed inference capabilities, including KV-cache management and data movement across heterogeneous hardware.
• Build representative benchmarks and workload traces that expose compute, memory, interconnect, networking, scheduling, and model-loading limits.
• Turn performance findings into regression tests and release gates in collaboration with test engineers.
• Inform hardware and software architecture where measurements reveal structural performance constraints.

Conhecimentos

C++

Python

Profiling

VFIO

Linux

Descrição da oferta de emprego

positron.ai is seeking an experienced engineer to improve end-to-end performance for large language model inference on custom accelerator systems. You will work across attention, data movement, and serving layers to optimize latency and throughput.

You will profile using counters and traces, develop distributed inference features including KV-cache management, and build benchmarks to expose limits. The role is remote-first in the United States with equity and comprehensive benefits.