Salesforce is experiencing rapid growth, with transactions increasing exponentially. The company needs to evolve its core infrastructure software to maintain speed, scale, and high availability. The Service Protection team is looking for a Machine Learning Engineer to apply ML to infrastructure software to address real-world availability and scalability challenges by detecting anomalies and automating resolutions.
Requirements
- Experience with deep neural networks and Gaussian processes
- Experience working with ML frameworks (Tensorflow, PyTorch, Keras)
- Experience working with Java and Python
- A solid understanding of both probability and statistics
- Strong mathematical skills and analytical skills
- Experience working with large amounts of data in a high throughput environment
- Experience working with Kafka or messaging/streaming tools
Responsibilities
- Use infrastructure data to asses, design, implement, train, and test machine learning models to detect anomalies
- Work closely with data and software engineers to apply machine learning model and scale to deploy anomaly detection models into our production infrastructure
- Design and implement major pieces of the salesforce.com core infrastructure, delivering high quality, production ready code
Other
- MS or PhD in Computer Science
- 5+ years of experience in one or more of the following areas: machine learning, recommendation systems, data mining
- Experience with agile software development, and short release cycle
