Avvir is solving some of the toughest problems in construction by providing detailed, reliable analytics of progress and quality for large construction projects. We are looking for a senior machine learning engineer to join the team iterating on the algorithms at the heart of our product.
Avvir is out to change the way we interact with the built environment. We create and continuously update a digital replica of buildings that serve as the building’s system of record. We do this by comparing the 3D design models (known as BIMs) that are created at the outset of a building’s construction to laser scans and 3D photos of the ever changing reality. During construction this enables stakeholders to identify construction errors and monitor progress in real time. And once a building is occupied, we enable that digital twin to serve as a platform for the internet of things, integrating data from hundreds of connected sensors in a common data environment.
We value and practice outcome over effort and respect for personal lives. We are headquartered in New York City. We have diverse backgrounds, encourage collaboration and teamwork, and cheer each other on. We work on an East Coast (US) schedule and are fully remote.
- In less than 12 months we’ve gone from $300k in ARR to $1.4m.
- We just completed our Series A.
- Our current customers love us. We have a 100% conversion rate from our pilot engagements over the last year.
- Someone who loves to learn & work collaboratively?
- Someone who has experience in both classical and deep ML techniques?
- Eager to solve hard problems with ML & Computer Vision?
- If so, then Avvir may be the right fit for you.
1) Work closely and pair with other developers to identify new research problems and iteratively improve our algorithms.
2) Promote practices and patterns that improve our ability to deliver and measure value.
3) Collaborate with product & design folks and product engineers to find the best path for delivering value.
- We cannot sponsor or transfer visas
- You have 6+ years of experience and perhaps a degree in a related machine vision / machine learning field.
- You have experience in both classical and deep ML techniques
- You have experience deploying ML models
- You can read, understand, and synthesize ideas from technical research papers
- You have coding experience and are comfortable jumping into our current stack:
- Python / Cython, Scipy, NumPy, Scikit-learn, TensorFlow / PyTorch
- You are excited to work in an agile, iterative way
- You care about code quality
- You are excited to use pair programming & TDD
- You can break down problems, communicate well, and empathize with users.
- Bonus points for:
- Experience with cloud architecture for ML Ops
- Experience with processing 2D image data or 3D geometric data
How we work:
- We keep tasks small and purpose focused with clear acceptance criteria so we can better manage and understand risks.
- We test-drive our code so that it’s easy to understand and change.
- We pair for a large portion of the day to facilitate learning, to write better code, and to reduce knowledge siloing.
- We are a remote-first team, and welcome candidates from anywhere in the US. Due to our high amount of collaboration, we require all developers to work our core working hours of 10-4 EST.
1) Apply here with your resume
2) 30 minute phone call to find out about your background
3) One hour 15 minute pairing exercise
4) One hour 30 minute ML problem solving interview
- At Avvir we believe in providing benefits that not only match our Avvir values (No Ego, Collaboration, Customer Obsessed, Personal Life Matters, and Outcome over Effort ) but that enhance the lives of our team members.
- We are a remote-friendly organization with a generous vacation policy (5 weeks vacation), fantastic health insurance plans, flexible work arrangements and equity options.
- We also offer a meaningful place to put your talents to work, expanding your job skills, and the ability to be a part of fundamentally changing the way construction is done. Plus you will get to work with some pretty cool people.