MLOps Engineer

Data Science
Tel Aviv
Full-time
Description

Fetcherr is an AI-driven company specializing in deep learning, algorithmic trading, and large-scale data solutions. Our core technology, the Large Market Model (LMM), enables accurate demand forecasting and real-time, data-driven decision-making. Originally focused on the airline industry, Fetcherr is expanding its AI solutions across additional industries.

We are looking for an MLOps Engineer to join Fetcherr’s engineering team and help build the foundations of large-scale, production-grade machine learning systems. This role is about owning complex ML infrastructure end-to-end — from data ingestion and feature engineering, through model training and deployment, to monitoring, reliability, and continuous improvement. You’ll work on systems that operate at scale, handle high-volume data, and directly impact real-time decision-making.

If you enjoy solving hard problems around scalability, reliability, automation, and ML in production, this role is for you.

Responsibilities: Building and operating end-to-end ML pipelines that support training, validation, deployment, and monitoring
Designing automated, reproducible ML workflows using CI/CD and infrastructure-as-code
Creating and maintaining data pipelines that handle large, complex datasets for ML workloads
Ensuring data and feature consistency between training and production environments
Designing and managing feature engineering workflows, including feature stores and versioning
Implementing model versioning, experiment tracking, and reproducibility standards
Monitoring model performance, data drift, and system health, and enabling automated retraining or alerting
Working closely with ML engineers to turn research into reliable, scalable production systems
Optimizing infrastructure for performance, cost efficiency, and scalability
Improving system reliability, observability, and developer productivity through automation and tooling
Taking part in architectural decisions that shape how ML is built and operated at Fetcherr
Requirements

You’ll be a great fit if you have...

5+ years of experience building production-grade systems, with a strong focus on Python
3+ years of experience in data engineering, working with large-scale data pipelines
Experience working with ML systems in production and applying MLOps best practices
Strong understanding of data structures and algorithms
Experience with distributed computing systems, preferably Dask
Experience with pipeline orchestration frameworks (Dagster, Prefect, Airflow – preferred)
Experience with containerized environments such as Docker and Kubernetes
BSc or MSc in Computer Science, Mathematics, or Engineering – preferred
Fluent English, written and spoken