Artificial Intelligence Engineer

Stelvio Inc.; Austin (TX); On-site; USD 140,000 - 220,000; Full time

Job summary

Stelvio Inc. in Austin is seeking seasoned AI/ML engineers to join a fast-growing AI startup. You will tackle technically demanding problems, own critical components, and influence core decisions alongside the CTO, shaping how the company builds its core technology.

We value engineers who can explain what they built, why they built it that way, what broke, and what they changed. Expect substantial ownership, production deployment challenges, and a path to technical leadership as the team scales.

Qualifications

• Experience designing, training or substantially adapting models with rationale behind architecture, data and training choices.
• Experience deploying AI systems, evaluating and improving in production, balancing quality with latency and cost.
• Ability to handle ambiguous requirements and interconnected systems requiring investigation.

Skills

Deep model development

Production engineering

Complex problem ownership

Technical leadership

Job description

Austin’s AI builders - what would make your next move worth it?

More difficult technical problems? Greater ownership? The opportunity to shape how an ambitious AI company builds its core technology?

I’m supporting an Austin-based AI start-ups that would like to connect with exceptional Lead, Principal and deeply experienced Senior AI/ML Engineers.

The conversations will centre on what you’ve personally built, the decisions you’ve owned, and how your systems performed when real customers depended on them.

The experience I’m keen to hear about:

• Deep model development: Designing, training or substantially adapting models, with a clear understanding of the choices behind the architecture, data and training approach.
• Production engineering: Taking AI systems through deployment, evaluation and ongoing improvement, balancing model quality with latency, reliability and cost.
• Complex problem ownership: Working through ambiguous requirements, difficult failure modes and interconnected systems where the answer takes investigation.
• Technical leadership: Setting direction, challenging assumptions and raising engineering standards while remaining close to the code.

You may have built this experience in a leading research or engineering organisation, an ambitious start-up, or across both. I’m particularly interested in engineers who can explain what they built, why they built it that way, what broke, and what they changed.

The appeal here is the scope: technically demanding work, substantial ownership and the opportunity to influence core AI engineering decisions directly with the CTO.