Machine Learning Engineer
Who are we?
Augmented Intelligence (AUI) is a tech company based in NYC with locations in Tel Aviv and Ramallah. We have developed a programming language that enables augmented intelligence. Since 2017, we have been building the operating system that will power the future of work. Backed by some of the most visionary investors in the world, we are creating a new work environment– one that couples the advantage of human agents (gumption) and AI (consistency). We have a culture that resembles a sports team, in which each member has tremendous ownership. We believe that work should feel like play. If you’re humble, hungry and have a big heart, this could be for you.
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, Amazon Kinesis or Apache Flink
- 2+ years of experience developing batch processing solutions using AWS EMR or alike
- 3+ years of experience writing production-grade Python code and working with both relational and non-relational databases
- 2+ years of experience writing production-grade SQL
- 2+ years of experience developing REST or PRC-based APIs
- 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
- Experience developing infrastructures that bring machine learning services to production using MLFlow or Amazon Sagemaker
- Experience orchestrating containerized applications in the AWS ecosystem using AWS ECS and ECR
- Experience working with graph databases such as Neo4j or Amazon Neptune
- Experience with workflow management frameworks, such as apache airflow.