Standard AI has revolutionized retail as we recognize it. Offering the first autonomous retail solution compatible with any existing store, customers can now walk in, pick up what they need, and walk out, eliminating waiting in lines or the need for physical payment. Our company's unique computer vision solution can be quickly and easily installed in pre-existing retail stores, rising as a significant advancement for retail technology and enabling retailers to swiftly provide new and astounding shopping experiences to customers. We've successfully launched dozens of stores in association with Circle K, Compass Group, and others, with hundreds more underway.
As the most well-funded enterprise in our sector, we are backed by premier Silicon Valley investors including SoftBank, CRV, Initialized, EQT, Draper Associates, and Y Combinator.
We are currently constructing a soft real-time machine learning system that enhances shoppers' checkout experience. Our system, which is solely vision-based, requires processing terabytes of video each day from hundreds of cameras using several interconnected models, pushing the limits of video comprehension to a new level.
Join us to contribute to our real-time production system that does real-time mapping, localization and classification of all store items, collaborating on complex tasks with our multi-view camera system, and solving graph optimization and difficult localization, segmentation and few-shot classification problems.
As a successful Machine Learning Engineer (MLE) at Standard, you will design and build top-notch production inference systems that directly affect our core business.
This position can be remote or in-person within the US, as Standard AI is a remote-first company. We value the freedom and flexibility of our employees to design work habits, locations, and schedules that cater best to their requirements.
Your role will involve:
- Contributing to the end-to-end development of ground-breaking machine learning systems.
- Solving modeling problems at the forefront of production machine learning.
- Collaborating cross-functionally with operation teams in data creation and labeling to design our extensive data sets.
- Contributing to our multi-view camera and 3D mapping code, solving challenging optimization, camera calibration, and SfM problems.
Requirements:
- 2+ years of experience in developing production software for Computer Vision systems.
- 4+ years of general engineering experience.
- Proven experience in implementing Machine Learning systems
- Excellent communication skills and ability to work across teams and time zones.
- Proactive problem-solving and flexible thinking abilities.
- Passionate about the entire ML lifecycle.
Perks:
- Full coverage of medical, dental, and vision premium by the employer. Generous contributions towards dependent premiums.
- A culture that emphasizes inclusivity. Employee Resource Groups, DEI focused training and resources, and opportunities for community service and engagement.
- Fertility and family planning assistance through Maven Clinic. Flexible scheduling for childcare needs and generous parental leave policies.
- Flexible Time Off for vacations, sick leave, mental health days, 12 company holidays plus 2 floating holidays.
We offer highly competitive compensation including stock options and world-class benefits. The total compensation package is dependent on factors such as location, level, related experience, and interview performance. Targeted starting salary for remote, USA is between $174,000 and $200,000 USD.
Standard is committed to equal employment opportunities for all employees and applicants, irrespective of race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We value diversity and inclusivity in our workforce and welcome people from all backgrounds, experiences, perspectives, and abilities. However, we cannot currently sponsor or take over sponsorship of an Employment Visa for this position. Applicants must be legally authorized to work in the United States for this opening.