Machine Learning Engineer

A successful startup in the Big Data field is a market leader in Data Security Posture Management. They have developed AI technology that easily and quickly connects to enterprise applications to autonomously identify and protect sensitive information.

Located in Tel Aviv, they offer a hybrid work model and have 200 employees globally, with about half based in Israel.

The company has raised approximately $500M in funding, with their latest fundraising round to be announced soon, positioning them for significant growth.

Role Description:

• Part of the Data Science (DS) team, focusing on engineering tasks during deployment in production.
• 80% of the time will be spent on models and Data Science content, and 20% on MLOps and DS/ML infrastructure.
• Work primarily involves LLMs and tabular data, deep learning for quantization and optimization.
• The role has an engineering focus, requiring software development-level coding in Python.
• Utilize MLOps tools and frameworks such as Airflow, DVC, MLflow, BentoML, Snowflake, Spark, Hadoop, and DL/ML libraries.
• Operate in a cloud environment, 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.
• 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.
• Knowledge of large language models (LLMs) and their applications is a plus.
• In-depth understanding of public cloud platforms (GCP/AWS/Azure) and their respective application architectures and technologies is a plus.