Inokyo · Remote, USA · Dec. 26, 2019
💰 $100,000 - $100,000 / yr
We are building state-of-the-art perception technology to blur the lines between the physical and digital world. Our mission is to create the most effortless shopping experience and establish a new global payments standard.
This all starts with automated retail checkout. By automating checkout using computer vision, Inokyo is building a digital interface for physical stores.
Detecting, localizing, and understanding each interaction in a store and associating them with the customer in real time with uncompromising accuracy is no easy feat and Inokyo is doing this today in retail stores.
We're looking for an experienced machine learning practitioner with strong theoretical understanding and exceptional programming ability.
You will work on novel approaches to number of challenging computer problems including person re-identification, multi-camera person localization + tracking, fine-grained object classification, and performant object detection + segmentation, among others.
As a machine learning engineer, you lead the entire life-cycle of our machine learning systems from ideation and experimentation to deployment in stores around the world.
Inokyo is a small team right now, so you'd be getting in right at the ground floor and have an enormous impact on the success and direction of the company and product.
- BA/BS degree in Computer Science or related technical field or equivalent practical experience.
- 2+ years of experience in computer vision or another machine learning driven field
- Demonstrated experience building models that meet the state of the art in accuracy and performance through published research or open source projects.
- You enjoy using the right programming language for the job and seamlessly transition between a number of them to balance performance, reliability and observability in your work.
- You should be comfortable with optimizing, debugging, and analyzing system critical code.
- Must have strong communication skills when talking about technical concepts. Our interview process strongly tests for communication as we have a very fast paced and collaborative work environment. Ideas and specifications are relayed quickly and clearly.