About Grabango - Who We Are
About The Role - What you'll be doing
We use computer vision, machine learning, and general feats of information processing to understand shopping, eliminate checkout lines, and save you time.
The experience of leaving a store without stopping to checkout feels like magic. We're making that magic happen behind the scenes by processing data gathered from distributed sensor networks, turning sets of isolated observations into coherent narratives.
This full-time role reports directly to the Engineering Manager, Computer Vision Team and is based in Berkeley.
As a Senior ML Infrastructure Engineer you will be supporting the computer vision team by building the infrastructure that bridges between research and production deployments. This will involve automating pipelines to deliver new deep learning models, building automation for retraining, and implementing production level monitoring. Additionally there will be opportunities to collaborate with other teams to find ways to improve the utilization of our services and improve our integration with other systems.
- Collaborating across multiple research and engineering disciplines to assess the technology tradeoffs required to rapidly deliver ML based software solutions
- Analyzing, designing and developing software for embedded and cloud platforms focused on solving complex and as novel machine learning problem
- Improving our production implementations and processes.
- Understanding our overall system and how the components our team builds fit.
- Leading new projects to build production services, analysis tools, development frameworks, and retraining data pipelines in support of computer vision, machine learning, and advanced algorithm development.
- 3+ years as a Machine Learning Engineer
- 3+ years experience using some combination of Python, C++, Java
- Ability to design and prototype software in simple, understandable code
- Familiarity with software engineering best practices in an Agile environment
- Experience designing, developing, and deploying RESTFull microservices
- An understanding of the computational trade offs needed for real-time machine learning applications
- Familiarity with libraries/packages/APIs (e.g. scikit-learn, Keras, PyTorch, TensorFlow, etc.)
- Familiarity with linux/unix
- Familiarity with different ML models (decision trees, random forests, support vector machines, neural networks, nearest neighbor, ensemble of multiple models, etc.)
- An understanding of how different ML pipeline pieces work together and how to communicate with them (using SQL database queries, REST APIs, etc.) and the ability to build appropriate interfaces for your component that others will depend on
- Experience with ML artifact management and Machine Learning model deployment.
- Familiarity with Google compute, Google Vertex, and MLFlow
Education & Certifications:
- Bachelor's degree or equivalent industry experience in a relevant field and demonstrated application of Machine Learning
- Masters preferred
Equal Opportunity Employer
Grabango is proud to be an equal opportunity employer and is committed to developing a workplace where diversity and inclusion are an essential part of who we are. We strive to hire and support a workforce as diverse as our shopper base, so we can develop products and services that best suit our customers. We do not make employment decisions based on race, color, religion, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status and we comply with all local, state and federal employment laws.
Grabango participates in the E-Verify Program, an internet-based system operated by the Department of Homeland Security and the Social Security Administration. It allows employers to confirm an individual’s employment eligibility to work in the United States.