At Standard Cognition, we’re rethinking the way retail works. We are enabling autonomous checkout for brick & mortar retailers with our AI-powered computer vision platform. Since launching in November 2017, Standard has contracts with multiple global retailers and is in the process of deploying our Standard Checkout solution across thousands of stores globally. We announced our Series A in November 2018 and we’re backed by some of Silicon Valley’s leading investors including CRV, Initialized, Draper Associates and YCombinator. Standard has raised its Series B and is valued at $535 million.

We're building a real time vision based scene comprehension engine in order to provide customers with a seamless checkout experience. We're looking for awesome Deep Learning Researchers to take ownership of individual models in this engine. We train our models on terabytes of multi-camera perspective video data which enables us to build and experiment with a huge diversity of research approaches. We love people who aren't afraid to jump around, so if you're background is in Vision, NLP, speech, or RL, that's great! We are researchers with all kinds of backgrounds, and find that a diversity of perspective helps the problem solving process.

You'll be iterating on new model architectures and novel research directions to handle complex shopping scenarios. You'll play a key role in identifying and addressing deficiencies in our datasets as well as devising metrics to optimize in order to maximize the overall accuracy for our customers.

A successful Deep Learning Researcher will iterate on lots of different approaches, and be able to identify the most promising avenues for further exploration. If this sounds like fun, we'd love to hear from you!

This is a FULL-TIME role is located onsite at our San Francisco office. 

What you'll do here:

•  Implement deep learning models for person detection, pose estimation, item classification, and action recognition
• Integrate latest research to test SOTA models on our custom datasets
• Devise models for aggregating visual and semantic features across multiple cameras perspectives and timescales
• Adapt pre-existing models to better handle the details of our particular problem set
• Experiment with model architectures, transfer learning strategies, data augmentation approaches, data sampling strategies, hyperparameter search
• Inspect model errors and formulate principled strategies to improve the accuracy of the system

Who you are:

• Masters/PhD in ML or related field OR 3+ years experience in ML
• Understanding of convolutional neural networks and the tradeoffs of different architectures, loss functions, and regularizers
• Experience implementing and training deep learning models
• Knowledge of best practices with respect to reproducible research and data hygiene
• Practical coding knowledge (Python preferred) to quickly iterate on training/testing pipelines
• Experience with reading academic machine learning literature
• Ability to think about what makes a good dataset that transfers to the real world
• Communicate clearly/concise
• Ability to problem solve in a flexible manner
• Technologies: Tensorflow, python, numpy

Only meet some of these traits or experiences? We'd still love to hear from you! 

Why you might want to work with us:

• We take care of you and your family with health, vision, and dental insurance.
• We're serious about food. Free catered lunch every day, and a fully stocked kitchen with occasional snack appearances from our Japanese office. Healthy and not-so-healthy options are available, as are foods for those with dietary restrictions.
• You're excited to work on a product that will impact almost any consumer, almost anywhere.
• We dress casually. If you want, you can wear slippers in the office. You should see the creative collection our team has built.
• We believe in a culture of learning, and want to keep building our skills, experiences, and capabilities.
• We offer flexible work schedules. We trust our team to know how they will do their best work.
• We're family friendly. We want our teammates to focus on what they need to when they need to.
• We offer very competitive compensation, including equity in Standard, to each one of our employees.

Standard provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.