Transparent Search Group Member of Technical Staff - Model Optimization and Inference Seattle, Washington, United States $250K–$350K View role

Company: Confidential - Venture-backed real-time AI research startup

Location: Seattle, WA (in office 5 days per week; relocation assistance available)

Compensation: $250,000 - $350,000 + equity

Employment Type: Full-time

Visa Sponsorship: Visa sponsorship available

About the Company

A venture-backed startup building real-time generative models for human-like audio and video interaction, founded by experienced AI researchers.

The Role

Our client is hiring an experienced ML Infrastructure/Systems Engineer (2+ years) to own end-to-end inference optimization across LLMs, audio models and diffusion components, with a focus on latency, throughput and cost.

What You Will Do

Own end-to-end inference optimization across the model stack.

Implement and tune KV cache strategies for long-context conversations.

Evaluate, deploy and extend serving frameworks such as vLLM, SGLang and TensorRT-LLM.

Profile and benchmark latency and throughput and remove bottlenecks.

Accelerate diffusion inference and apply quantization techniques (INT8, INT4, GPTQ, AWQ).

Build internal tooling that makes optimization work faster and more rigorous.

What You Bring

2+ years building and maintaining production ML systems

Designing scalable infrastructure from scratch

Track record optimizing latency, throughput and cost

Debugging distributed systems

Nice to Have

Video or audio model experience

CUDA kernels and low-level optimization

Real-time video streaming (WebRTC)

Benefits

HSA with about $2,000 annual company contribution, 15 days PTO plus public holidays and a company-wide office closure week.

Tech Stack

Kubernetes, Terraform, Python, Rust, Go, Dagster, Ray, Airflow, WebRTC, vLLM, Triton Inference Server, TensorRT