Staff ML Engineer: Applied AI for Industrial Solutions

Circuit; Austin (TX); On-site; USD 180,000 - 270,000; Full time

Job summary

Circuit is seeking a Staff Engineer, Applied ML in Austin, TX to build ML capabilities powering our industrial product. You’ll collaborate with Forward Deployed Engineers, Product Engineers, and design customers to translate real-world challenges into scalable ML solutions.

You’ll own end-to-end delivery, balancing accuracy, latency, and cost while shaping product capabilities for multiple customers. You will work with LLMs, traditional ML, and a mix of models, ensuring robust evaluation,

Qualifications

• Strong software engineering fundamentals and ability to ship end-to-end production systems.
• Deep experience with data modeling across relational and graph databases.
• Hands-on experience building with LLMs, RAG systems, and agent harnesses.
• Experience working with customers to turn feedback into product features.
• Ability to generalize a solution to multiple customers.
• Proficiency in Python and Go.
• Experience with AI coding tools and prompt iteration.

Responsibilities

• Work directly with FDEs and design-customers end to end, to build solutions on top of Circuit that solve their challenges.
• Generalize and package our solutions and methods, and empower FDEs to efficiently deploy them across customers.
• Improve our underlying models, harnesses, eval methodologies and more to power our solutions and help solve customer challenges.
• Debug production systems including edge cases and failure modes in ML pipelines and retrieval systems.
• Build and maintain evaluation systems, including datasets, scoring approaches, and repeatable testing to detect regressions.

Skills

Python

Go

PyTorch

LLMs

RAG systems

AI deployment

Tools

KServe

vLLM

CPUs/GPUs

Job description

Circuit is seeking a Staff Engineer, Applied ML in Austin, TX to build ML capabilities powering our industrial product. You’ll collaborate with Forward Deployed Engineers, Product Engineers, and design customers to translate real-world challenges into scalable ML solutions.

You’ll own end-to-end delivery, balancing accuracy, latency, and cost while shaping product capabilities for multiple customers. You will work with LLMs, traditional ML, and a mix of models, ensuring robust evaluation,