Member of Technical Staff, Exceptional Generalist (Remote)

Inferact; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary and equity

Visa sponsorship

Health coverage where applicable

Job summary

A cutting-edge technology company is looking for exceptional generalist engineers who thrive with autonomy. This fully remote role allows you to work on high-impact projects across the vLLM stack, from optimizing CUDA kernels to designing distributed orchestration systems. Ideal candidates will have a Bachelor's degree and a strong track record in systems programming or ML infrastructure. Competitive compensation and benefits are offered.

Qualifications

• Ability to work autonomously and drive projects to completion.
• Excellent communication skills across time zones.
• Deep expertise in systems programming, GPU programming, or distributed systems.
• Strong track record of shipping high-impact work in complex technical environments.
• Deep expertise in at least one of: systems programming, GPU/accelerator programming, distributed systems, or ML infrastructure.

Responsibilities

• Work across the entire vLLM stack from GPU kernels to distributed systems.
• Optimize CUDA kernels and design orchestration systems.
• Build foundational layers for distributed systems at global scale.
• Collaborate across time zones to deliver high-impact ML infra projects.

Skills

Autonomy

Asynchronous communication

Systems programming

GPU/accelerator programming

Distributed systems

ML infrastructure

Education

Bachelor's degree or equivalent experience

Tools

CUDA

Rust

Go

C++

Python

Kubernetes

Job description

Overview

Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference cheaper and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware—a position that took years to build.

About The Role

This is a globally remote opportunity. We're seeking exceptional generalist engineers who can work across the entire vLLM stack: from low-level GPU kernels to high-level distributed systems. This role is designed for self-directed, autonomous individuals who can identify the highest-leverage problems and solve them end-to-end without constant guidance.

You\'ll work asynchronously with our San Francisco headquarters while maintaining full ownership of critical infrastructure. You might be optimizing CUDA kernels one week, designing distributed orchestration systems the next, and implementing new model architectures the week after. The work you do will directly impact how the world runs AI inference.

Potential focus areas

• Inference Runtime: Push the boundaries of LLM and diffusion model serving. Work at the core of vLLM to optimize how models execute across diverse hardware and architectures.
• Kernel Engineering: Write the low-level kernels and optimizations that make vLLM the fastest inference engine in the world, running on hundreds of accelerator types.
• Performance & Scale: Build the distributed systems that power inference at global scale—design foundational layers enabling vLLM to serve models across thousands of accelerators with minimal latency.
• Cloud Orchestration: Build the operational backbone for cluster management, deployment automation, and production monitoring that enables teams worldwide to serve AI models without friction.

What We're Looking For

We\'re looking for engineers who thrive with autonomy. You should be able to take a vague problem statement and turn it into shipped code with minimal supervision. You communicate proactively, over-communicate context across time zones, and know when to ask for help versus when to push forward independently.

Core Requirements

• Bachelor\'s degree or equivalent experience in computer science, engineering, or similar
• Demonstrated ability to work autonomously and drive projects to completion without close supervision
• Excellent asynchronous communication skills and ability to collaborate effectively across time zones
• Strong track record of shipping high-impact work in complex technical environments
• Deep expertise in at least one of: systems programming, GPU/accelerator programming, distributed systems, or ML infrastructure

Technical Depth (strong in at least two)

• CUDA kernels or equivalent (Triton, TileLang, Pallas) with deep understanding of GPU architecture
• High-performance distributed systems in Rust, Go, or C++
• Python with PyTorch internals and LLM inference systems (vLLM, TensorRT-LLM, SGLang)
• Kubernetes, container orchestration, and infrastructure-as-code at scale
• Transformer architectures, KV-cache memory management, and model serving

Preferred Qualifications

• Contributions to vLLM or other major open-source ML/systems projects
• Experience with multiple accelerator platforms (NVIDIA, AMD, TPU, Intel)
• Knowledge of quantization techniques, ML-specific kernel optimization, or compiler technologies
• Track record of improving system reliability and performance at scale
• Written widely-shared technical blogs or impactful side projects in the ML infrastructure space

Logistics

• Location: Fully remote, worldwide. We\'re timezone-flexible but expect regular overlap with Pacific Time for critical syncs.
• Compensation: We offer competitive compensations (salary + equity) compared to the local market conditions.
• Visa sponsorship: We sponsor visas on a case-by-case basis.
• Benefits: Inferact offers competitive benefits appropriate to your location, including health coverage where applicable.