Staff / Principal Machine Learning Engineer, Serving

Inworld AI; Mountain View (CA); On-site; USD 270,000 - 500,000; Full time

Benefits offered by this job

Relocation assistance

Equity options

Comprehensive benefits package

Job summary

A tech-driven AI firm in Mountain View is seeking a high-performance systems engineer. This role demands expertise in inference optimization, model acceleration, and a deep understanding of performance tuning in C++, CUDA, and more. Candidates should possess a PhD or equivalent experience. Compensation ranges from $270,000 to $500,000 plus bonuses and equity. Relocation assistance is provided for successful candidates looking to innovate in a collaborative atmosphere.

Qualifications

• Deep understanding of modern serving frameworks like vLLM or TRT-LLM.
• Hands-on experience with quantization and caching strategies.
• Proficiency in profiling code and optimizing performance for NVIDIA GPUs.

Responsibilities

• Take models from research, containerize and optimize for production.
• Communicate and collaborate closely with the team.
• Design prototypes to explore unclear problems.

Skills

Inference Optimization

Model Acceleration

High-Performance Systems

Distributed Systems & Scaling

Public work

Full-cycle ownership

PhD in CS, Physics, Math or equivalent

Education

PhD in Computer Science or equivalent

Tools

C++

CUDA

Rust

Python

Kubernetes

Job description

Who We're Looking For

A year ago, reliably working agentic systems and sub-second multimodal inference at scale barely existed. Nobody has a decade of experience here. So we're not screening for a resume template — we're looking for strong people from varied backgrounds who learn fast, thrive in ambiguity, and can show us what they've built, broken, and understood.

Experience We Find Useful

You don't need all of this. But you need enough to make a case.

• Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM.
• Model Acceleration. Hands-on experience with quantization, distillation, caching strategies, continuous batching, paged attention, and speculative decoding.
• High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs.
• Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections.
• Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups.
• Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production.
• Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems.

Who Thrives Here

• You don’t need a roadmap to start walking; you’re comfortable picking a direction and building the map as you go.
• You believe engineering isn't finished until it’s shipped and stable. You have a bias for impact over purely theoretical optimizations.
• You don't just ship code; you obsess over the why. You’re the first to question an architecture if you think there’s a better way to solve the core latency or throughput problem.
• You aren't satisfied with "the PM said so." You thrive on deep context and want to understand the fundamental logic behind every decision we make.

What Working Here Is Like

We hand you unclear problems and expect you to make them clear. We value engineers who say "I don't know yet" and then design the benchmark or prototype that finds out. We treat performance, latency, and reliability as first-class product features, not a box to check before launch. Impact comes before everything else, though we support sharing work and open-source contributions that move the field forward. Your work should be visible. Flat structure, fast iterations, minimal process theater.

We believe in the power of in-person collaboration to solve the hardest problems and foster a strong team culture. We offer relocation assistance and look forward to you joining us in our Mountain View office.

Compensation & Benefits

The base salary range for this full-time position is $270,000 - $500,000+ bonus + equity + benefits.