Machine Learning engineers build basic statistical and machine learning models, and create mechanisms to implement these models into large data sets.
In this position, you’ll:
- Research and build analysis methods applicable to data collected by USERGRAM
- Preprocess large data sources
- Perform basic analysis to understand trends and features of data and its visualization
- Choose the right data sets and data representation for analysis
- Perform feature engineering according to the purpose of data analysis and data set
- Build data aggregation mechanisms and machine learning models
- Function proposal of application related to data analysis and machine learning
- Implement the built-in data aggregation mechanism and machine learning model in the product
- Model evaluation of data analysis and tuning to improve accuracy
- Train and retrain the data analysis models (if needed)
- Extend our Machine Learning library and framework
- Stay up to date with the latest information on data science and AI
You should have:
- Experience as a machine learning engineer or a similar role
It would be nice if you have:
- Experience with large-scale distributed processing using Hadoop and Spark
- Data aggregation experience using Athena or BigQuery and database design experie nce for tables and partitions
- ETL development experience such as AWS Glue and CLOUD DATAFLOW
- Experience with container orchestration systems using Kubernetes
- Experience using NoSQL servers such as Cassandra and DynamoDB
- Data processing experience using distributed messaging systems such as Apache Kafka and Amazon Kinesis
We are looking for someone who:
- Has not only have technical skills, but can also relate to our vision for USERGRAM
- Discovers product issues themselves and proposes improvements
- Has an interest in the design of the whole service, including the working with other teams
- Communicates with team members and shares knowledge about services and technologies
- Eliminates technical debt and makes small improvements on a regular basis
