Staff Machine Learning Engineer
Zscaler is seeking a Staff Machine Learning Engineer to join our Exposure Management & Security Operations team in Bangalore. This role involves designing and deploying scalable, reliable, and efficient production-grade Generative AI and Machine Learning systems, from data ingestion to monitoring. The successful candidate will drive innovation by researching and evaluating emerging AI/ML frameworks, rapidly prototyping novel solutions, and championing full-scale implementation. Additionally, the role includes implementing and maintaining robust MLOps practices, such as logging, monitoring, and CI/CD pipelines for distributed ML systems. The engineer will lead and mentor junior engineers in system design best practices and promote technical excellence, while collaborating with cross-functional teams to translate complex business needs into technical solutions.
The ideal candidate will have at least 5 years of experience as a Machine Learning Engineer, with a proven track record of shipping complex, scalable ML systems to production. They should have experience building Generative AI/ML systems with Large Language Models (LLMs), fine-tuning, Retrieval-Augmented Generation (RAG), and Agentic AI in production environments. A strong foundation in computer science, including data structures, algorithms, and system design, is essential, along with expertise in Python and SQL. Excellent communication and interpersonal skills are required to effectively partner across global engineering teams.
Preferred qualifications include expertise with cloud services such as AWS, GCP, or Azure, and ML platforms like Kubeflow or SageMaker. Proficiency in systems programming languages like Go or Rust, with an understanding of distributed systems and networking fundamentals, is also desirable. A record of research, publications, or patents in AI/ML will be considered a strong asset.
Zscaler offers a comprehensive benefits program to support employees and their families, including various health plans, time off plans for vacation and sick time, parental leave options, retirement options, education reimbursement, and in-office perks. We are committed to building a team that reflects the communities we serve and fostering an inclusive environment that values all backgrounds and perspectives.