Role Locations
- Remote
- San Francisco, CA, United States
Employees
Address
Tech Stack
- Go
- Python
- Docker
- Tensorflow
- PyTorch
- Keras
- Kubernetes
- PostgreSQL
- AWS
- Azure Cloud
- Google Cloud Platform
- React
- TypeScript
Role Description
As an Applied Machine Learning Engineer, you will be one of our resident experts for machine learning and model development. Combined with an extensive knowledge of our open-source platform, you will help our users solve a wide range of problems in machine learning development, from exploratory data analysis to model deployment. Additionally, you will collaborate with our engineering teams to ensure our software meets our users' needs. Finally, your understanding of the machine learning landscape will inspire our product and engineering direction to ensure our open-source platform continues to be at the cutting edge of MLOps.
About Determined AI
We build a high-performance ML development environment that enables ML engineers to train better models more quickly, to seamlessly utilize and manage large GPU clusters, and to collaborate more easily with their teammates. Determined allows ML engineers to focus on doing ML at scale, rather than managing infrastructure or writing boilerplate code.
We work at the intersection of large-scale distributed systems and cutting-edge machine learning. Our customers are highly skilled ML engineers and domain experts working on exciting problems in biotech, hardware design, autonomous vehicles, and more. We interact with them to learn more about their data sets, modeling problems, and infrastructure, to help them with our product, and to improve our product offering.
After 4 years as a startup company, we were recently acquired by Hewlett Packard Enterprise (HPE). At HPE, we will remain a distinct organization — we'll be building the same product targeting the same users. Plus we'll have access to HPE's customers, hardware products, and resources to take our mission to the next level.
Company Culture
We believe the best ideas can come from anyone and anywhere, and we have to be humble enough to listen for them. We are customer-focused, but don't think the customer is always right. We are excited about the latest in ML and distributed systems research but try to implement the minimum valuable product. We believe in open communication and transparency in our process and priorities. We believe in the healing power of karaoke and hot sauce.
Address
Tech Stack
- Go
- Python
- Docker
- Tensorflow
- PyTorch
- Keras
- Kubernetes
- PostgreSQL
- AWS
- Azure Cloud
- Google Cloud Platform
- React
- TypeScript
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