Fundamental Research Labs
Member of Technical Staff - ML
Fundamental Research Labs, Menlo Park, California, United States, 94029
About the Role
As a Member of Technical staff focused on ML, you’ll push the limits of frameworks, refine our agent architecture, and build the benchmarks that define performance at scale. You’ll help take our frontier models from the lab into lightning-fast production-ready services.
If you relish experimenting with the latest serving research, building optimizations, and shipping infrastructure for researchers, then we invite you to apply!
Responsibilities
Architect and optimize high-performance inference infrastructure for large foundation models
Benchmark and improve latency, throughput, and agent responsiveness
Work with researchers to deploy new model architectures and multi-step agent behaviors
Implement caching, batching, and prioritization to handle high-volume requests
Build monitoring and observability into inference pipelines
Qualifications
Strong experience in distributed systems and low-latency ML serving
Skilled with performance optimization tools and techniques, and experienced in developing solutions for critical performance gains
Hands‑on with vLLM, SGLang, or equivalent frameworks
Familiarity with GPU optimization, CUDA, and model parallelism
Comfort working in a high‑velocity, ambiguity‑heavy startup environment
What makes us interesting
Small, elite team
of ex‑founders, researchers from top AI Labs, top CS grads, and engineers from top companies
True ownership
You will not be blocked by bureaucracy, shipping meaningful work within weeks rather than months
Serious momentum
We're well‑funded by top investors, moving fast, and focused on execution
What we do
Ship
consumer products powered by cutting‑edge AI research, and
Build
infrastructure that facilitates research and product, and
Innovate
cutting‑edge research that will open up new consumer product forms
The Details
Full‑time, onsite role in Menlo Park
Startup hours apply
Generous salary, with additional benefits to be discussed during the hiring process
#J-18808-Ljbffr
If you relish experimenting with the latest serving research, building optimizations, and shipping infrastructure for researchers, then we invite you to apply!
Responsibilities
Architect and optimize high-performance inference infrastructure for large foundation models
Benchmark and improve latency, throughput, and agent responsiveness
Work with researchers to deploy new model architectures and multi-step agent behaviors
Implement caching, batching, and prioritization to handle high-volume requests
Build monitoring and observability into inference pipelines
Qualifications
Strong experience in distributed systems and low-latency ML serving
Skilled with performance optimization tools and techniques, and experienced in developing solutions for critical performance gains
Hands‑on with vLLM, SGLang, or equivalent frameworks
Familiarity with GPU optimization, CUDA, and model parallelism
Comfort working in a high‑velocity, ambiguity‑heavy startup environment
What makes us interesting
Small, elite team
of ex‑founders, researchers from top AI Labs, top CS grads, and engineers from top companies
True ownership
You will not be blocked by bureaucracy, shipping meaningful work within weeks rather than months
Serious momentum
We're well‑funded by top investors, moving fast, and focused on execution
What we do
Ship
consumer products powered by cutting‑edge AI research, and
Build
infrastructure that facilitates research and product, and
Innovate
cutting‑edge research that will open up new consumer product forms
The Details
Full‑time, onsite role in Menlo Park
Startup hours apply
Generous salary, with additional benefits to be discussed during the hiring process
#J-18808-Ljbffr