Senior Machine Learning Engineer, Computer Vision
Standard AI has transformed retail as we know it. With the first autonomous retail solution that works in any existing store, we enable customers to walk in, grab what they need, and walk out - without waiting in line or stopping to pay. The company’s computer vision solution is the only one that can be quickly and easily installed in retailers’ existing stores, representing a giant leap forward for retail tech that enables retailers to rapidly deliver amazing new shopping experiences to customers. Standard has launched dozens of stores alongside Circle K, Compass Group, and others and have hundreds more on the way. We’re the most well funded in our space, backed by some of Silicon Valley’s leading investors including SoftBank, CRV, Initialized, EQT, Draper Associates, and Y Combinator.
We're building a soft real-time machine learning system that provides shoppers with a seamless checkout experience. Our system is vision only, and every store must stream process terabytes of video per day from hundreds of cameras, touching on a multitude of interconnected models. We're pushing the limits of what video comprehension can achieve, and we're expanding to do it at scale. You'll help us solve problems that few teams have ever tackled.
You’ll help build our production system that does real time mapping, localization and classification of all items in a store in real time. This role blends challenging tasks with our multi-view camera system, graph optimization problems, and hard localization, segmentation as well as few shot classification problems. Like other Machine Learning Engineer (MLE) roles at Standard, you will partner closely with full stack engineers, product managers, and operational teams to drive critical business impact.
As a successful MLE at Standard, you will design and build high-quality production inference systems that impact our core business. All our ML Engineers contribute to the full life cycle of model development, from cross-functional data set acquisition, to training pipelines, to model design, to scaling out model serving and monitoring. If this sounds like fun, we'd love to hear from you!
This is a full time role and can be based remotely anywhere within the US on an ongoing basis. Standard AI is a remote first company. We want our employees to have the flexibility to create work habits, locations, and schedules that best fit their lives.
What you'll do here:
- Contribute to the end to end development of state of the art machine learning systems, from metric definition and data set creation to model deployment and monitoring
- Solve modeling problems at the cutting edge of production machine learning
- Work cross-functionally with operation teams in data creation and labeling to help design our massive data sets
- Contribute to our multi-view camera and 3D mapping code, solve challenging optimization, camera calibration, and SfM problems
Who you are:
- 2+ years of experience building production software for Computer Vision systems, preferably with localization, segmentation, and few shot classification problems
- 4+ years of general engineering experience
- Experience in implementation of Machine Learning systems and familiarity with deep learning methods
- A clear communicator who excels working across teams and time zones
- A proactive problem solve and flexible thinker
- Passionate about the entire ML lifecycle
Why you might want to work with us:
- 100% employer-paid medical, dental and vision premiums, as well as generous contributions towards dependent premiums.
- An inclusive culture. Employee Resource Groups, DEI focused training and resources, and opportunities for community service and engagement.
- Fertility and family planning assistance provided through Maven Clinic, as well as flexible scheduling to accommodate for childcare needs and generous parental leave policies.
- Flexible Time Off to be used for vacations, sick time and/or mental health days, 12 US Company Holidays plus 2 additional Floating Holidays.
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.
Applicants must be legally authorized to work in the United States for this opening. We are unable to sponsor or take over sponsorship of an Employment Visa for this position at this time.