Zscaler
Senior Machine Learning Engineer
Zscaler, San Jose, California, United States, 95199
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.
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. This role offers a remote work option.
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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. This role offers a remote work option.
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