Staff Machine Learning Engineer - Agentic AI

Zscaler; Bengaluru; On-site; INR 1,800,000 - 2,500,000; Full time

Benefits offered by this job

Various health plans

Time off plans

Parental leave options

Retirement options

Education reimbursement

In-office perks

Job summary

Zscaler is seeking a Staff Machine Learning Engineer to join its Exposure Management & Security Operations team in Bangalore. This hybrid role requires expertise in designing and deploying scalable ML systems, with a focus on innovation and MLOps practices. The ideal candidate has at least 5 years of experience, a strong foundation in computer science, and proficiency in Python and SQL. Zscaler offers comprehensive benefits to support its employees and their families.

Qualifications

• At least 5 years of experience as a Machine Learning Engineer with a track record of shipping complex, scalable ML systems to production.
• Proven experience building Gen AI/ML systems with LLMs, fine-tuning, RAG, and Agentic AI in production environments.
• Strong computer science foundation in data structures, algorithms, and system design.

Responsibilities

• Design and deploy scalable Gen AI/ML systems from data ingestion to monitoring.
• Drive innovation by researching and evaluating emerging AI/ML frameworks.
• Implement MLOps practices, including logging, monitoring, and CI/CD pipelines.

Skills

Machine Learning Systems

MLOps

Python

SQL

Communication Skills

Tools

AWS

GCP

Azure

Kubeflow

SageMaker

Job description

Role

We are looking for a Staff Machine Learning Engineer to join our Exposure Management & Security Operations team. This role is a hybrid position based in Bangalore, reporting to the Sr. Manager, Engineering Strategy, Planning & Analytics. You will join the team that built the world’s largest cloud security platform from the ground up, helping to scale a multitenant architecture that serves over 15 million users globally. Your vision and passion will be critical as we continue to innovate and enable organizations to harness the speed and agility of a cloud‑first strategy.

What you’ll do (Role Expectations)

• Designing and deploying scalable, reliable, and efficient production‑grade Gen AI/ML systems from data ingestion to monitoring
• Driving innovation by researching and evaluating emerging AI/ML frameworks, rapidly prototyping novel solutions, and championing full‑scale implementation
• Implementing and maintaining robust MLOps practices, including logging, monitoring, and CI/CD pipelines for distributed ML systems
• Leading and mentoring junior engineers in system design best practices and promoting technical excellence
• Collaborating with cross‑functional teams to translate complex business needs into technical solutions

Who You Are (Success Profile)

• You thrive in ambiguity and are comfortable building the path as you walk it, seeing dynamic environments as the raw material to build something meaningful.
• You act like an owner with a passion for the mission and a bias for action, navigating seamlessly between high‑level strategy and hands‑on execution.
• You are a problem‑solver who seeks out challenges because you are energized by finding solutions that deliver the biggest impact.
• You are a learner with a growth mindset, actively seeking feedback to become a better partner and a stronger teammate.
• You are driven by innovation and have a deep curiosity for how things work, believing in the power of technology to accelerate transformation.

What We’re Looking for (Minimum Qualifications)

• At least 5 years of experience as a Machine Learning Engineer with a track record of shipping complex, scalable ML systems to production
• Proven experience building Gen AI/ML systems with LLMs, fine‑tuning, Retrieval‑Augmented Generation (RAG), and Agentic AI in production environments
• Experience designing and implementing distributed ML systems with deep knowledge of MLOps, including monitoring and logging
• Strong computer science foundation in data structures, algorithms, and system design with expertise in Python and SQL
• Excellent communication and interpersonal skills to partner effectively across global engineering teams

What Will Make You Stand Out (Preferred Qualifications)

• 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
• A record of research, publications, or patents in AI/ML

Benefits

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

• Various health plans
• Time off plans for vacation and sick time
• Parental leave options
• Retirement options
• Education reimbursement
• In‑office perks, and more!

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules.

Accommodations

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy‑related support.

Equal Employment Opportunity Statement

Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information: Know Your Rights: Workplace Discrimination is Illegal (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)