Senior Machine Learning Engineer

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 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 general and administrative teams help to support and scale our great company. Whether striving to grow our workforce, nurture an amazing culture and work environment, support our financial and legal operations, or maintain our global infrastructure, the G&A team provides a strong foundation for growth. Put your passion, drive and expertise to work with the world's cloud security leader.

We are looking for a Machine Learning Engineer with strong expertise in applied modeling to design, implement, and optimize machine learning solutions. The ideal candidate will excel at building robust predictive models and deploying scalable systems to solve real-world business challenges. This role offers an exciting opportunity to directly impact Zscaler's data-driven initiatives and drive innovation across the organization. You will be reporting to the Senior Manager, Data Science, working as an individual contributor. You will:

• Develop and deploy end-to-end machine learning pipelines, from data preprocessing to model deployment.
• Design and implement applied ML models for LLM, predictive analytics, anomaly detection, and optimization, etc.
• Collaborate with cross-functional teams, including data engineers and product developers, to integrate models into production systems.
• Analyze large datasets to uncover actionable insights and improve model performance.
• Stay updated on advancements in machine learning and adapt them to solve practical business problems.

What We're Looking for (Minimum Qualifications)

• Bachelor’s or advanced degree in Computer Science, Machine Learning, Statistics, or a related field, with 5+ years of applied experience in machine learning and data modeling.
• Proficient in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn), with expertise in statistical modeling techniques like regression, clustering, and decision trees.
• Hands-on experience deploying ML models in production using modern tools, combined with strong data manipulation and analysis skills; familiarity with visualization tools like Matplotlib or Tableau.
• Demonstrated problem-solving abilities and capability to work independently on complex tasks.

What Will Make You Stand Out (Preferred Qualifications)

• Experience with big data technologies like Hadoop and Spark, and proficiency in cloud platforms such as AWS, Azure, or GCP.
• Knowledge of deep learning techniques, neural network architectures, and domain-specific AI solutions like NLP.
• Understanding of MLOps best practices for scalable model deployment and monitoring.

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This role offers remote work option

Zscaler’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.

At Zscaler, we believe that diversity drives innovation, productivity, and success. We are looking for individuals from all backgrounds and identities to join our team and contribute to our mission to make doing business seamless and secure. We are guided by these principles as we create a representative and impactful team, and a culture where everyone belongs. For more information on our commitments to Diversity, Equity, Inclusion, and Belonging, visit the Corporate Responsibility page of our website.

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 proud to be an equal opportunity and affirmative action employer. We celebrate diversity and are committed to creating an inclusive environment for all of our employees. All qualified applicants will receive consideration 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 characteristics 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. For additional information about the federal requirements, click here.

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.