Zscaler is looking to enhance its Digital Experience team by hiring an experienced Sr. Machine Learning Engineer to build agentic AI features and resilient services for its cloud security platform.
Requirements
- BS in CS (or related) with 4+ years experience, or MS with 2+ years, delivering ML/GenAI features to production
- Exceptional problem-solving skills driven by first-principles thinking, applying expertise in programming, data, and machine learning
- Proven experience in the full ML model lifecycle— building, deployment, monitoring, and optimization
- Hands-on experience with modern GenAI stacks (e.g., LangChain/LangGraph, CrewAI, vector stores, RAG, prompts/memory, evaluators)
- Solid distributed systems fundamentals (APIs, queues, caching, concurrency) and cloud experience (Docker/Kubernetes, CI/CD; AWS/GCP/Azure)
- Prior delivery of agentic/LLM systems in production, including context engineering and memory management strategies
- Experience fine-tuning and serving LLMs/SLMs at scale (latency, cost, safety, evals)
Responsibilities
- Build agentic AI features: implement tool-use workflows (planning, memory, context), retrieval/RAG, and evaluators; harden for scale and reliability
- Ship resilient services: design and operate microservices, data/feature pipelines, and low-latency inference paths with solid observability
- Operate with excellence: add tests, monitors, tracing, dashboards; participate in on-call with an automation-first mindset
Other
- This role is hybrid and based in our San Jose, CA office three days a week.
- Reporting to the Sr. Director, Software Engineering
- Named a Best Workplace in Technology by Fortune and others, Zscaler fosters an inclusive and supportive culture that is home to some of the brightest minds in the industry.
- If you thrive in an environment that is fast-paced and collaborative, and you are passionate about building and innovating for the greater good, come make your next move with Zscaler.
- Zscaler is committed to providing equal employment opportunities to all individuals.
