Your opportunity
We are the Anomaly Detection team. We are a blend of pure engineering (high throughput, distributed services in JVM languages) and applied research (Python, Statistical Methods, and Machine Learning).
Our team focuses on detecting and analyzing anomalous behavior by identifying unexpected changes or deviations in data, as well as proactively extending the detection coverage for our customers. As a part of our AIOps solution, we provide tools to help customers analyze these issues and reduce the mean time to resolution. This aligns with our vision ‘We support high availability systems by automatically detecting and remediating problems while constantly optimizing. When human intervention is required, we provide teams with the most relevant degree of contextual information’.
Work our team has shipped includes time series dynamic baselines alerting, NRQL query facet suggestion, Error Profiles, and Proactive Detection.
Please note that visa sponsorship is not available for this position.
What you'll do
Our ideal candidate is someone who can strengthen our team with their knowledge and passion for data science and machine learning to build outstanding products that delight our customers. Our team of engineers are responsible to ship reliable data science and ML solutions at scale. If you join our team you will:
- Research, develop, and prototype statistical and data science solutions to model our customers’ production systems, to detect and help explain unusual behavior
- Debug and support our models from an operational standpoint
- Own our product, from concept to operations. We ship high-quality software and ensure our services are reliable and are on-call for the services we own
- Create and maintain distributed high-throughput applications in JVM languages, using frameworks such as Kafka and stream processing technologies such as Flink.
This team collaborates with product management, product designers, technical support, and engineering team to frame problems with business and product context and breaks down that work into concrete tasks. You will have work-life balance that enables you to thrive by using unlimited flex time-off, twelve weeks of paid parental leave, and our DataNerds4Good volunteer time off program!
This role requires
- 4+ years of professional work experience with software engineering teams or equivalent experience building, operating, and owning modern systems in Java.
- Hands-on experience and knowledge of machine learning techniques and algorithms using Python or R
- Experience having developed and shipped high-throughput, fault-tolerant, multi-threaded applications in a production environment
- Have a keen eye for quality; ability to write unit tests for all their code and considers what type of automated testing is appropriate
- Comfortable working on a team where code quality and code reviews are prioritized
Bonus points if you have
- Applied statistics skills, ability to reason about time series analysis data is a plus
- Experience developing software for the public Cloud, preferably AWS is a plus
- Experience with Kubernetes/Docker is a plus
- Experience advocating for improvements to architecture and clearly articulating reasons why and assessing tradeoffs