AI Engineer
Summary
Cambio is seeking an AI Engineer to build and deploy AI-powered features for their real estate decarbonization platform. The role involves managing end-to-end AI pipelines, optimizing model performance through evaluation frameworks, and collaborating on production-grade generative AI solutions.
About Cambio
Cambio is a software platform for real estate decarbonization. We help commercial real estate owners bring their portfolios to net-zero with an AI-driven sustainability, asset, and investment management platform. We're backed by Y Combinator, Google, and Stanford — and we're the fastest-growing startup in our category.
The role
We're looking for an AI Engineer to build AI-powered features, help teammates do their best work, and have fun doing it.
What you'll be doing
Build AI features end-to-end, from prototype to production
Design and run evals to measure and improve model/feature quality
Build and maintain data + inference pipelines that power AI features in production
Experiment with new models, prompting, and retrieval approaches to improve accuracy and cost
Support and collaborate with your teammates
Who you are
An A-player: low ego, curious, and serious about your craft
You are outcome driven
Work isn't in opposition to life for you - it's part of your life because you genuinely enjoy it
You ship through obstacles — roadblocks are part of the problem to solve
You move with urgency and close the week with visible impact
You're relentlessly curious and treat truth-seeking as a discipline
You believe iteration speed is quality - the way to build great things is to build fast and learn faster
You show up for your teammates, in person. You unblock before being asked and never let someone stay stuck
You own your work end-to-end - proactive about visibility, proud of your progress, and you over-communicate until everyone is fully aligned
What do you bring
Experienced in Python web development (Django is a bonus)
Someone who's shipped AI features and understands the eval challenges that come with them
Hands-on experience with LLMs/generative AI (prompting, fine-tuning, or RAG)
Comfortable with evaluation frameworks and measuring model quality in production
Familiar with vector databases and retrieval-based architectures
Understands the tradeoffs between model cost, latency, and accuracy
What we offer
Competitive compensation and startup equity
Flexible time off
$1,200 annual learning budget
Catered lunch
Best workstation in beautiful offices in Waterloo, New York, and San Francisco
As published by ashby
Name, Email, Resume, Location
- LinkedIn URL
- Are you legally authorized to work in the United States or Canada? yes / no
- Will you now or in the future require sponsorship for employment visa status (e.g., H1B visa status)? yes / no
- I acknowledge and consent to the interview being recorded for note-taking and evaluation purposes. yes / no
- Travel may be required for offsites and quarterly planning sessions, please share any travel restrictions below.