Senior ML Engineer — Real-Time AI, Equity & Relocation

Inworld, Inc.; Mountain View (CA); On-site; USD 250,000 - 300,000; Full time

Benefits offered by this job

Relocation assistance

Job summary

Inworld, Inc. is hiring for a full-time role in Mountain View, CA to advance real-time AI systems at scale. You will optimize inference and model serving, implement acceleration techniques, and own end-to-end deployment from research to production.

The position values deep expertise in C++/CUDA/Rust and distributed architectures, with a PhD or equivalent practical experience as a strong asset. You will contribute to high-performance, multi-GPU deployments, collaborate across teams, and help

Qualifications

• Experience with modern serving frameworks and techniques (e.g., vLLM, TRT-LLM)
• Hands-on quantization, distillation, caching, batching, attention, decoding
• Proficient in C++, CUDA, Rust, or optimized Python for NVIDIA GPUs
• Experience with Kubernetes, Ray, multi-GPU/multi-node inference
• Contributions to open-source inference engines or deep-dive technical write-ups
• Ability to take a model from research to production and ensure reliability

Responsibilities

• Take models from research to production and containerize them.
• Optimize serving latency, throughput, and reliability in production environments.
• Collaborate across teams to ship high-performance AI systems.

Skills

Inference optimization

Model acceleration

High-performance systems

Distributed systems

Open-source contributions

Full-cycle ownership

PhD or equivalent experience

Education

PhD or equivalent practical experience

Tools

C++

CUDA

Rust

Python

Job description

Inworld, Inc. is hiring for a full-time role in Mountain View, CA to advance real-time AI systems at scale. You will optimize inference and model serving, implement acceleration techniques, and own end-to-end deployment from research to production.

The position values deep expertise in C++/CUDA/Rust and distributed architectures, with a PhD or equivalent practical experience as a strong asset. You will contribute to high-performance, multi-GPU deployments, collaborate across teams, and help