Explainable AI Platform for the Enterprise
We created Fiddler because we understand the implications of AI, and the potential danger of not having visibility into how it affects the real world. We believe there is a need for a new kind of AI platform, that is highly transparent, trustable and operational.
What you'll do:
- Design and build a world-class Cloud Platform to help ML engineers and Data Scientists build and deploy Deep Learning Models with high productivity and velocity
- Build a modern runtime stack for Deep Learning supporting formats like Tensorflow, ONNX, PyTorch etc.
- Develop cluster automation to manage a fleet of TensorFlow workers via Kubernetes
- Work with Customer Data Scientists to understand their requirements and design and build a world-class ML Platform to improve their productivity and velocity
- Recommend adjustments to resolve software issues, improve the functionality of existing software, and ensure that the design, application, and maintenance of software meets quality standards
- Continuously look for ways to improve service performance and incorporate user feedback to design and build a better product.
- Provide training, mentoring, and guidance to other engineers and engineering interns
What we're looking for:
- BS/MS/PhD in Computer Science or equivalent
- Proficiency with programming languages (Python, Java)
- Expertise in working with at least one deep learning framework,such as PyTorch, Torch, TensorFlow, Caffe
- A track record for delivering Machine Learning projects for a product
- Knowledge of infrastructure management (AWS / Google Cloud, Kubernetes, or equivalent on-premises technologies)
- Curiosity, ownership, empathy towards customers, willingness to learn new things and desire to inspire others are values we care
Fiddler Labs is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees
Fiddler Labs at a glance
Fiddler Labs focuses on Cloud Computing, Artificial Intelligence, Big Data Analytics, Distributed Systems, and Deep Learning. Their company has offices in San Francisco Bay Area. They have a small team that's between 11-50 employees.