Machine Learning Engineer
Engineering – Machine Learning
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 Machine Learning Engineers to work on the core components of our machine learning ecosystem. We train a variety of machine learning models on terabytes of data, deploy them in a live-inference setting, and must do so in a scalable, efficient way for all of our stores. If you have a background in Machine Learning and enjoy engineering challenges, this role is a unique opportunity to work at the cutting edge of building machine learning systems.
A successful Machine Learning Engineer will build high-quality production systems that drive key improvements to our machine learning ecosystem and ultimately produce more accurate and efficient models at scale. This role interacts heavily with our research and pipeline team members. 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:
- Build systems for automated training, deployment, and management of machine learning models
- Integrate machine learning models into our realtime streaming pipeline
- Optimize performance of machine learning systems, including training and inference workflows
- Build machine learning dataflows for optimized i/o
- Experiment with different data transformation, feature creation, and aggregation strategies
- Build tools for automated validation and visualization of machine learning models and data quality
- Work on our data visualization and inspection suite
Who you are:
- You have 3+ years experience and at least 1 year in the machine learning industry
- You have experience working on live inference machine learning systems
- You have experience building optimized data workflows for inference and/or batch offline processing
- You are experienced in systems programming
- Technologies: Systems Programming, Tensorflow (or experience using Sci-kit learn), scientific python (SciPy, NumPy), Rust (or experience with a systems language), OpenCV+
- You have knowledge of best practices with respect to reproducible research and data hygiene
- Ability to think about what makes a good data set, reduction of bias
- You communicate clearly and possess the ability to work cross-functionally with other teams (models, pipeline, tracking, mapping)
- Ability to problem solve in a flexible manner
Only meet some of these requirements? 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.