- New York
- $120k - $180k
- 0.25% - 1.00%
We’re looking for someone to join our small engineering team building a system of record for buildings. We compare photographs and laser scans of construction sites to building plans to assess building completion and verify things are being built to plan. We raised our seed round in APril and are looking to expand our engineering team. We are looking for someone who can work as part of a team to implement cutting-edge algorithms for a variety of geometric processing and learning tasks.
This is a full time position in New York City ideal for someone with at least a Master's degree (Ph.D preferred) in a related computer vision / machine learning field.
The ideal candidate has experience in processing 2D image data or 3D geometric data and is well-versed in both classical and deep ML techniques. Experience in our scientific computing environment is a bonus:
Python / Cython, OpenCV, Scipy, NumPy, Scikit-learn, TensorFlow / PyTorch, Google Cloud, Jenkins, Docker, *nix
1) Work closely and often pair with other engineers on implementing, evaluating, and improving our technology.
2) Collaborate with Design/Product team to find the best path for delivering value. We are relentlessly focused on creating a great service. On a balanced team, everyone is responsible for respecting the expertise of others, but also sharing their expertise and contributing to the direction of the product.
3) Communicate current blockers and progress with product manager / team.
4) Keep current on the latest techniques by reading and presenting research articles
How we work:
We keep stories small and acceptance criteria clear so we can better manage and understand risks. We test-drive our code so that it’s easy to understand and change. We pair up about 15 hours/week to facilitate learning, to write better code, and to reduce knowledge siloing.
We are also always working on improving the way that we work, and every week we have a retrospective to reflect and consider ways we could be doing things better.
- A Master's degree (Ph.D preferred) in a related machine vision / machine learning field.
- Experience in processing 2D image data or 3D geometric data and is well-versed in both classical and deep ML techniques.
- Detailed knowledge of current research trends and understanding of applicable academic publications.
Experience in our scientific computing environment is a bonus:
Python / Cython, Scipy, OpenCV, NumPy, Scikit-learn, TensorFlow / PyTorch, Google Cloud, Jenkins, Docker, *nix
Experience in computational geometry would also be a great plus.
General knowledge of Construction Industry (Preferred, but not required)
Perks & Benefits
At Avvir we believe in providing benefits that not only match our Avvir values (Decency, Passion for the Work, Personal Life Matters, and Outcome over Effort ) but that enhance the lives of our team members. We are a remote-friendly organization with an unlimited vacation policy, 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.
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 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're still a pretty small team working on defining our values but we believe the following: We believe your job should enrich your life, not take it over. We believe in working smart over working hard (though hard work isn’t bad.) We believe you can only be truly successful when you are fulfilled and empowered; your work should fulfill you and colleagues should empower one another. And we believe in being decent, to one another, and in general.
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