Zscaler
AI

Sr. Staff ML Engineer

Zscaler · Remote · $147k - $210k

Actively hiring Posted about 1 year ago

About Zscaler
Serving thousands of enterprise customers around the world including 40% of Fortune 500 companies, Zscaler (NASDAQ: ZS) was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. As the operator of the world’s largest security cloud, Zscaler accelerates digital transformation so enterprises can be more agile, efficient, resilient, and secure. The pioneering, AI-powered Zscaler Zero Trust Exchange™ platform, which is found in our SASE and SSE offerings, protects thousands of enterprise customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
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. 
Our Engineering team built the world’s largest cloud security platform from the ground up, and we keep building. With more than 100 patents and big plans for enhancing services and increasing our global footprint, the team has made us and our multitenant architecture today's cloud security leader, with more than 15 million users in 185 countries. Bring your vision and passion to our team of cloud architects, software engineers, security experts, and more who are enabling organizations worldwide to harness speed and agility with a cloud-first strategy.
We're looking for a Sr. Staff Machine Learning (ML) Engineer to join our AI Copilot team. This role will be based in our San Jose, CA office (hybrid, 3 days per week in office). Reporting to the Sr. Manager, you'll be responsible for:

Developing and implementing use cases for the AI Copilot to be utilized by IT administrators, cybersecurity operations, and vulnerability management teams, focusing on both efficiency and user experience.
Conducting in-depth research on the latest advancements in GenAI technologies and applying these cutting-edge techniques to build AI Copilot use cases.
Designing, building, and deploying distributed micro-services, ensuring scalability and robustness.
Collaborating closely with Product Managers and customers to design high-value use cases that meet business objectives and drive product innovation.

What We’re Looking for (Minimum Qualifications):

8+ years of experience delivering end-to-end AI/ML solutions in production.
Proficiency with mainstream modeling toolkits, including ML/Deep learning (TensorFlow/Keras, PyTorch, Sklearn, Spacy), Data Science (Pandas, Numpy, Spark), and LLM frameworks (HuggingFace, Langchain, Nvidia Nemo stack).
Solid experience in scalable and distributed system design, with a track record of implementing systems or frameworks with high throughput, resilience, and modularity.
Proficient knowledge of full-stack languages and frameworks, such as Python, ReactJS, Java (Framework: FARM Stack, MERN Stack, Spring Stack).
Familiarity with cloud-native DevOps, including practices and tools like Jenkins, Kubernetes (K8s), Docker, Helm, Istio, and Terraform.

What Will Make You Stand Out (Preferred Qualifications):

Experience in training language models (LLM or SLM) for production usage.
Experience or enthusiasm in cybersecurity or digital transformation.

#LI-Hybrid #LI-AZ2Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.
The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.Base Pay Range$147,000 - $210,000 USDAt Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.
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!

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.
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 by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.
Pay Transparency
Zscaler complies with all applicable federal, state, and local pay transparency rules.
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.

Tags & focus areas

Used for matching and alerts on DevFound
Engineer Machine Learning Ai Senior Docker Java Kubernetes Tensorflow Pytorch Remote
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.