Senior ML Engineer

Cyera is on a mission to protect one of the world's most valuable resources: data. Our AI-native platform gives organizations a complete view of where their data lives, how it’s used, and how to keep it safe, so they can reduce risk and unlock the full value of their data, wherever it is.

Since our founding in 2021, we’ve grown fast- Cyera-fast - securing over $760 million in funding from the biggest pockets on the planet and establishing a global team. Today, Cyera is the fastest growing data security company in the world, trusted by the Fortune 500 and beyond.

About The Role

We are looking for a talented and experienced ML Engineer with a strong interest in data science to join our team. The ideal candidate will have a solid background in both data engineering and backend development, with a passion for optimizing deployed models and building data and ML infrastructure tools.

What You’ll Do

• Develop and maintain scalable, production-ready infrastructure for Large Language Models (LLMs): This includes working with both open-source and proprietary tools to ensure efficient and reliable deployment of LLMs in a high-volume environment.
• Optimize LLM performance: Analyze and optimize LLM performance through techniques such as model distillation, quantization, and efficient data structures, ensuring optimal efficiency and resource utilization.
• Stay updated on the latest advancements in machine learning and data classification techniques.
• Collaborate with data scientists and engineers to ensure seamless integration of models into existing infrastructure or create a new one.
• Perform code reviews and provide technical guidance to other team members.
• Contribute to the development and improvement of data science tools and frameworks used by the team.
• Contribute to open-source projects: Actively engage with the open-source community by contributing code, documentation, and expertise to relevant LLM projects, fostering innovation and knowledge sharing.
  
  

• 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.