MLOps Engineer

Department
AI
Type
Full-time
Level
Location
Israel
About The Position

MLOps Engineer

Fetcherr experts in deep learning, algo-trading, e-commerce, and digitization, Fetcherr disrupts traditional systems with its cutting-edge AI technology. At its core is the Large Market Model (LMM), an adaptable AI engine that forecasts demand and market trends with precision, empowering real-time decision-making. Specializing initially in the airline industry, Fetcherr aims to revolutionize industries with dynamic AI-driven solutions.

We are seeking an MLOps Engineer to help us grow our technical team's capabilities. The ideal candidate has relevant experience in data engineering, preferably within the AI field. Aviation industry experience would be a great addition.

You will be responsible for building and maintaining data pipelines that power our data science workflows. You'll play a crucial role in ensuring the accuracy, consistency, and efficiency of the data we use for model training and inference. This involves working with both structured and unstructured data from various sources, leveraging your expertise in data engineering and machine learning to create a robust and scalable system.

About The Position

You’ll be a great fit if you have:

BSC or Master's degree in Computer Science / Math / Engineering is preferable
At least 5 years of commercial experience in Python – must
At least 3 years hands-on data engineering commercial experience - must
Familiar with MLOps and AI domain
Experience working with pipelines orchestrators, preferably Dagster, Prefect or Airflow
Good understanding of Data Structures and Algorithms
Basic knowledge of Docker and Kubernetes or other, scalable, containerized solutions
Team player, ready to help others
Pro-active with the tasks given to you, often suggesting different / better ideas
Commercial experience working with Dask (preferred) or other distributed computing systems – must
Commercial experience in writing and maintaining scalable systems
English – fluent, both written and spoken