Senior Machine Learning Engineer, Inference
Quick Summary
Own the optimization process from research models to production deployment. Improve latency and throughput for real-time voice and LLM inference at consumer scale.
At least 5 years of experience in ML inference or systems engineering, at a senior level equivalent to Google L5 or Meta E5.
Join a high-performing engineering team developing advanced real-time voice and large language model (LLM) technology. As a Senior Machine Learning Engineer, you will own inference optimization from research through production deployment, helping bring sophisticated models to consumer-scale applications. You will tackle complex challenges involving latency, throughput, GPU efficiency, and distributed serving infrastructure. Working directly with modern inference engines, you will apply cutting-edge acceleration techniques to improve performance and scalability. You will collaborate closely with research and product teams to turn innovative models into reliable production systems. This is an opportunity to make a significant technical impact on AI products serving hundreds of millions of users.
You will lead end-to-end inference optimization, ensuring that advanced machine learning models perform efficiently and reliably in production environments. Your responsibilities will include:
-
Own the optimization process from research models to production deployment.
-
Improve latency and throughput for real-time voice and LLM inference at consumer scale.
-
Work directly with inference engines such as vLLM, TensorRT-LLM (TRT-LLM), and SGLang to enhance performance.
-
Implement model acceleration techniques, including quantization, distillation, speculative decoding, caching, continuous batching, and paged attention.
-
Develop high-performance GPU workloads using C++, CUDA, Rust, or optimized Python.
-
Build and scale distributed multi-GPU and multi-node inference systems using Kubernetes, Ray, and custom load-balancing solutions.
-
Collaborate with research and product teams to bring new models into production.
Requirements
~1 min readThe ideal candidate is a senior-level machine learning inference or systems engineer with strong hands-on experience optimizing production inference engines and building scalable GPU infrastructure. You should bring:
-
At least 5 years of experience in ML inference or systems engineering, at a senior level equivalent to Google L5 or Meta E5.
-
Practical experience optimizing inference engines such as vLLM or TRT-LLM at the engine level, beyond basic model deployment.
-
A proven background in developing backend and machine learning systems and serving models in production.
-
Strong systems programming and GPU optimization skills using C++, CUDA, Rust, or optimized Python.
-
Hands-on knowledge of model acceleration techniques, including quantization, distillation, speculative decoding, caching, continuous batching, and paged attention.
-
Experience with distributed systems, Kubernetes, Ray, load balancing, multi-GPU and multi-node inference, and high-concurrency environments.
-
Excellent English communication skills.
-
Residence in the United States, Canada, the United Kingdom, Germany, Switzerland, or Serbia.
Additional advantages include a track record of rapid career progression, contributions to open-source inference engines or technical publications, and a PhD in Computer Science, Physics, or Mathematics, or a degree from a leading computer science program. The ability to commute to Mountain View, California, is also a plus.
What We Offer
~1 min readLocation & Eligibility
About this job
- Pay per year
- $250,000–$300,000 a year
- 32% above the $208,788 median for Machine Learning Engineer jobs on Jobera (1,008 salaries).
- Who can apply
- United States
- Posted
- Today
Listing Details
- Posted
- November 5, 2026
- First seen
- November 5, 2026
- Last seen
- November 5, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 80%
- Scored at
- November 5, 2026
Signal breakdown
Similar Machine Learning Engineer jobs
View all →Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.