Senior Machine Learning Architect
About The Position
If you love to design and build machine learning based products on massive real-time data streams, this job is for you.
Anodot provides real time analytics, automated anomaly detection and forecasting that discovers outliers in vast amounts of time series data and turns them into valuable business insights.
Analyzing the massive quantity of metrics generated by today’s businesses – manually or with traditional business intelligence tools – takes time and expertise. Using patented machine learning algorithms, Anodot forecasts and isolates issues and correlates them across multiple parameters in real time, eliminating business insight latency and supporting rapid business decisions through its uncovered insights.
We are looking for a Senior Machine Learning Architect to join our data science team.
What you’ll do:
- Lead the end-to-end architecture, development and operation of machine learning solutions in production.
- Architect and develop highly scalable, distributed solutions.
- Solve problems using a diverse technology stack including Apache Airflow, TensorFlow, Kubernetes, Docker, AWS and more.
- Implement machine learning algorithms.
What you have:
- Experience designing and implementing large scale production systems
- Experience with: Pandas/NumPy (must), ML framework (e.g. sklearn / TensorFlow)
- Ability to work in cloud environment (e.g. AWS / k8s) on data infrastructure such as Apache Airflow, Cassandra, relational DBs, Spark
- Relevant BSc (Computer Science, Math, Statistics)
- Team player with good communication skills – required for knowledge transfer among team members
- At least 5 years’ experience developing Python and Java
- Experience with time series modeling, unsupervised learning algorithms (clustering, anomaly detection, etc) and Deep Neural Nets for time series - Significant advantage
- Experience with: TensorFlow, Pytorch, Ray, Dask
- Cloud infrastructures: AWS services, Docker, Kubernetes
- MSc or PhD – significant advantage