Machine Learning Engineer
What will you be doing?
- Architect, Design, and implement infrastructures and tools to enable AI research and deployment within the AWS ecosystem
- Develop batch and streaming pipelines that fuel machine learning services
- Architect complicated jobs and orchestrate them on managed services
- Install and update disaster recovery procedures to safeguard our data
- Integrate techniques to constantly improve data reliability and quality
Who you are?
A seasoned software engineer who’s experienced in all layers of the data hierarchy – from database design to data collection and storage techniques, to a deep understanding of data transformation tools and methodologies, to provisioning and managing of analytical databases, to building infrastructures that bring machine learning capabilities into production.
What should you have?
- 2+ years of experience developing real-time stream processing solutions using Apache Kafka or Amazon Kinesis – Must
- 2+ years of experience developing infrastructures that bring machine learning services to production using Amazon Sagemaker and AWS EMR – Must
- Demonstrated experience orchestrating containerized applications in the AWS ecosystem using AWS ECS and ECR – Must
- 3+ years of experience Writing production-grade Python code and working with both relational and non-relational databases
- Solution orientation and ‘can do’ attitude – with a sense of ownership and accountability
- Bachelor’s Degree in Computer Science, Engineering or a similar computational discipline
- High English skills
- Bonus: Experience in modeling and developing machine learning models
- Bonus: Experience working with graph databases such as Neo4j or Amazon Neptune
- Bonus: Experience with Snowflake Data Warehouse