Machine Learning Engineer

A startup company in the Big Data field has developed AI technology that easily and quickly integrates with enterprise applications to autonomously identify and protect sensitive information.

Located in Tel Aviv, near a train line, the company offers a hybrid work model with two work-from-home days. They have 200 employees globally, with about half based in Israel.

The company is funded with around $500M, and their latest funding round will be announced soon, as they are in a strong growth phase.

About the role-

• The role is part of the Data Science team and involves engineering work in the deployment stages of production.
• Work focuses on models and Data Science content, emphasizing MLOps and DS/ML infrastructure.
• Most tasks revolve around LLMs and tabular data.
• Involves deep learning for quantization and optimization.
• Engineering-focused role with software development primarily in Python.
• Work includes using MLOps tools such as Airflow, DVC, MLflow, BentoML.
• Involves technologies like Snowflake, Spark, Hadoop, and various ML/DL libraries.
• The role includes working in a Cloud environment.
• Focus on improving model performance and infrastructure.

Requirements-

• 5 years of experience in a backend or ML engineering role with a demonstrable track record of successfully deploying code in production environments.
• 3 years of development experience in Python.
• Experience with big data technologies such as Snowflake, Spark, Hadoop, or similar, for processing and analyzing large datasets.
• Hands-on experience with MLOps tools such as Airflow, DVC, MLflow, BentoML, Lammaindex, ZenML, or similar tools for managing the machine learning lifecycle.
• Passion for building custom tools from scratch to solve our unique challenges and improve ML workflows.
• Strong problem-solving skills and ability to take ownership of tasks from conception to full implementation, working both independently and collaboratively within a team.

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