Senior ML Engineer

Come join the company reinventing data security, empowering businesses to realize the full potential of their data. As the leading data security platform purpose-built for the cloud era, Cyera’s mission is to reinvent how businesses secure data, enable agile collaboration, and boldly pursue new business opportunities. Trusted by security teams at leading global businesses, our team is proving that data security is the next big thing in cyber. Backed by the world’s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data security.

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. 

Responsibilities

• 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.