Principal Machine Learning Engineer
San Jose, California, United States
Zscaler
Zscaler is the leader in cybersecurity and zero trust digital transformation. Transform your IT and security needs with the best CASB and SASE solutions.About Zscaler
Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company’s cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances.
Zscaler 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. Zscaler’s purpose-built security platform puts a company’s defenses and controls where the connections occur—the internet—so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside.
Job Description
At Zscaler, our AI and Data Science teams focus on various cybersecurity business-centric use cases including threat detection, policy recommendation, malware detection, content classification, anomaly detection, and AIOps (advanced networking diagnosis). As a Principal Data Scientist, you will have the opportunity to work on multiple fundamental machine learning problems addressing cloud security, cloud operations, and cloud intelligence.
You will be responsible for leading the development and implementation of advanced machine learning models, mentoring junior team members, and driving strategic AI and data science initiatives. You will have a deep understanding of various stages of an end-to-end Machine Learning project and will be capable of translating business problems into data-driven solutions.
Responsibilities
- Lead the development of advanced machine learning models to address complex business problems
- Mentor and guide team members on projects and professional growth
- Collaborate with cross-functional teams to define project objectives and deliverables
- Design, implement, and evaluate innovative machine learning solutions, ensuring alignment with business objectives
- Drive strategic initiatives, identifying opportunities for improvement and innovation
- Applied research: Stay up-to-date and apply the latest advancements in machine learning and data science
- Communicate complex data science concepts to non-technical stakeholders and drive data-driven decision-making across the organization
Required Skills
- 8+ years of experience as a Machine Learning Engineer or Data Scientist, with a proven track record of leading and delivering successful projects
- Expertise in Python (e.g., pandas, sklearn, pytorch) and SQL
- Extensive experience in feature engineering, model evaluation, and error analysis
- In-depth knowledge of Large Language Models (LLMs) and their applications
- Master's or Ph.D. in Computer Science/Engineering or other technical field; data science concentration is a plus
- Strong passion for leveraging ML/AI to solve real-world business problems at scale
- Exceptional interpersonal, technical, and communication skills
- Proven ability to learn, evaluate, and adopt new technologies quickly
- Solid computer science foundation
Preferred Skills
- Experience in prompt engineering and fine-tuning Large Language Models (LLMs)
- Expertise in Graph Neural Networks/Knowledge Graphs
- Proficiency in unsupervised learning (clustering) and evaluation
- Research experience/publications/patents in relevant areas
- Familiarity with public cloud services (such as AWS, Google, Azure) and ML automation platforms (such as Kubeflow)
- Proficiency in various programming languages such as (Py)Spark
- Deep understanding of operating systems and distributed systems
- Knowledge of networking and networking security concepts
#LI-JM1
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.
Base Pay Range$212,500—$250,000 USDBy 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.
Tags: Agile AWS Azure Classification Clustering Computer Science Distributed Systems Engineering Feature engineering Kubeflow LLMs Machine Learning ML models Pandas Privacy Prompt engineering Python PyTorch Research Scikit-learn Security Spark SQL Unsupervised Learning
Perks/benefits: Career development Equity Health care Salary bonus
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