Join Cartesia as an Inference Engineer to design and build low latency, scalable model inference for cutting-edge AI applications.
Posted by employer 1 year ago
First seen on Joblaze 1 month ago
Last verified on the company career page 12 hours ago
AI in the day-to-day
Engineers work on building real-time multimodal intelligence using advanced AI models.
Requirements
- Education
- PhD
- Visa
- Sponsorship available
Not disclosed in this posting: compensation, years of experience.
Benefits
Joblaze summary
The Inference Engineer at Cartesia focuses on designing and building a low-latency, scalable inference stack for advanced AI models, ensuring reliable performance across various applications. Key skills include strong engineering capabilities, experience with distributed systems, and familiarity with machine learning inference pipelines. This role is ideal for someone with a technical leadership background who thrives in ambiguous environments and is eager to contribute to cutting-edge AI solutions. Cartesia's collaborative culture emphasizes fast execution and high-quality design.
Joblaze insights
Quick facts
- Is the Inference Engineer role remote?
- No — this is an on-site role in *HQ - San Francisco, CA.
- Where is the role based?
- Cartesia is hiring for this position in *HQ - San Francisco, CA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: CUDA, SGLang, SSMs, Transformers, Triton, vLLM.
- Does Cartesia sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Cartesia targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Inference Engineer role at Cartesia.
From the original posting
About the Role
We're hiring an Inference Engineer to advance our mission of building real-time multimodal intelligence.
Your Impact
Design and build low latency, scalable, and reliable model inference and serving stack for our cutting edge foundation models using Transformers, SSMs and hybrid models.
Work closely with our research team and product engineers to serve our suite of products in a fast, cost-effective, and reliable manner.
Design and build robust inference infrastructure and monitoring for our products.
Have significant autonomy to shape our products and directly impact how cutting-edge AI is applied across various devices and applications.
What You Bring
Given the scale and difficulty of problems we work on, we value strong engineering skills at Cartesia.
Strong engineering skills, comfortable navigating complex codebases and an eye for writing clean and maintainable code.
Experience building large-scale distributed systems with high demands on performance, reliability, and observability.
Technical leadership with the ability to execute and deliver zero-to-one results amidst ambiguity.
Background in or experience working on inference pipelines with machine learning and generative models.
Experience implementing state of the art Machine Learning models and research to applied problems.
Preferable: experience with vLLM, SGLang, Continuous Batching or other inference frameworks.
Preferable: experience working in CUDA, Triton or similar
🏦 401(k)
🦖 Your own personal Yoshi
Standard company text repeated across Cartesia's postings is omitted here.