Senior Computer Vision Engineer

2 weeks ago


Walnut Creek, United States Burnt Island Ventures Full time

Who are we:

SewerAI is an AI and data management platform that is improving the speed, effectiveness and cost for cities and engineering firms to manage infrastructure. Our cutting edge AI lowers the total cost of ownership of cities’ infrastructure by reducing the dirty, dull and dangerous work that must be done to maintain infrastructure.

Formed in 2019, we are a VC funded early stage startup, looking to hire an AI Engineer to join our team who wants to work on our entire machine learning pipeline that helps SewerAI deliver real-time insights to cities around the world and to ourselves.

About The Job

We are looking for an AI engineer to work on our entire machine learning pipeline. The ideal candidate should have a passion for AI and be ready to learn on the job. Deep learning is a rapidly evolving field, and working in AI is a process of constant learning and exploration – what is considered state of the art changes extremely quickly. We need someone ready to dive into the messy jungle of real world data, with all its noise, inconsistencies, and variation.

You'll be at the cutting edge of deep learning, applying state-of-the-art models to our specific domain to tackle unique challenges and develop dependable production systems.

Although we primarily work with videos, projects may involve other data types such as tabular and point cloud datasets.

This is a hybrid position, candidates must live in the bay area and be in office 1-2 days per week.

Preferred Qualifications

Real world experience putting vision AI into volume production. A Masters degree in a quantitative field or equivalent in work experience Familiarity with machine and deep learning (e.g. supervised/unsupervised learning, training/validation/test sets, classification/regression, metrics, neural networks, loss functions, optimization, data augmentation, transfer learning) Familiarity with modern computer vision techniques – convolutional neural networks, ResNets, object detection, vision transformers Basic knowledge of linear algebra, calculus, and statistics (matrix manipulation, derivatives and integrals, statistical distributions, performance metrics) Experience with PyTorch Strong Python knowledge Experience with Python data science stack – Pandas, Numpy, Scipy, Jupyter, data visualization Strong verbal and written skills, ability to communicate effectively with all levels throughout the organization and effectively present results Results driven, with strong analytical and problem solving skills Ability to read, discuss, and implement new research papers Willingness to learn:

SQL, Docker, REST APIs and a backend framework (e.g. Django, Flask) to access datasets. Distributed training/inference management using cloud technologies like AWS, GCP, Azure. Wastewater infrastructure inspection domain knowledge Working alongside the AI Team, you will:

Analyze and manage data Research and Experiment with new AI architectures and systems Produce reports and visualizations depicting system performance Assist in Managing the ML Production Pipeline Collaborate to develop requirements Participate in agile development process Salary & Perks

Tools you need to get the job done Competitive salary and potential equity-based remuneration Budget for courses, books, conferences – your development is important to us Why SewerAI:

SewerAI is applying AI to the massive problem of sewer overflows. Most people aren't aware but our sewer infrastructure is crumbling around us, leaking enough sewage nationwide to cover the entire SF bay area in 7" of raw sewage.

We are revolutionizing the antiquated industry by automating the labor intensive part of labeling cracks, roots and grease in pipeline inspection videos.

We are a Series A funded startup with a large and growing client base looking for a talented engineer to help improve our AI system.

Come join a startup that is solving a real world problem with AI.

Equal Employment Opportunity Employer #J-18808-Ljbffr



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