Staff Data Scientist

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 Summary:

Zscaler is seeking an experienced and innovative Data Scientist specializing in Generative AI to join our dynamic team. The ideal candidate will possess in-depth knowledge and practical experience with Large Language Models (LLMs), AI operations (AI Ops), AI toolchains, Retrieval-Augmented Generation (RAG), fine-tuning techniques, and model evaluation methodologies. You will play a crucial role in advancing our AI-driven products and services, leveraging cutting-edge AI technologies to drive forward-thinking solutions and advancements.

• Be a part of a startup team in the company, working on creating a new product.
• Engage in the development of state-of-the-art Gen AI technology

Key Responsibilities:

• Advanced LLM Development:
  • Implement and enhance Large Language Models using techniques like Retrieval-Augmented Generation (RAG) for improved context understanding and response generation
  • Continuously refine and fine-tune AI models to cater to specific use cases and improve overall performance
• AI Ops and Toolchain Optimization:
  • Manage AI operations to ensure efficient deployment and maintenance of AI models.
  • Optimize AI toolchains for streamlined development, testing, and deployment of AI solutions.
• Comprehensive Model Evaluation:
  • Develop and implement robust model evaluation frameworks to assess model performance, accuracy, and reliability.
  • Conduct thorough testing and validation of AI models to ensure they meet high-quality standards.
• Data Analysis and Algorithm Development:
  • Analyze vast datasets to extract meaningful insights and inform model improvements.
  • Create and implement advanced machine learning algorithms tailored to specific AI applications.
• Cross-Functional Collaboration:
  • Collaborate with various teams to integrate AI technologies into diverse products and services.
  • Lead innovation initiatives and contribute to the company's AI strategy and vision.
• Documentation and Knowledge Sharing:
  • Maintain comprehensive documentation of methodologies, experiments, and findings.
  • Share knowledge and insights with team members and stakeholders, ensuring transparency and collaborative growth.

Personal Attributes:

• Exceptional analytical and problem-solving skills.
• Effective communication and collaboration abilities.
• Adaptable to rapidly changing technologies and environments.
• Deep passion for AI research and continuous learning.

Qualifications:

• PhD or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
• 8+ years of industry experience
• Extensive experience with Large Language Models, including RAG and fine-tuning techniques.
• In-depth knowledge of AI Ops, AI toolchains, and model evaluation methods.
• Proficient in machine learning, deep learning, and statistical modeling.
• Strong programming skills in Python, R, or similar languages.
• Familiarity with AI frameworks (e.g., TensorFlow, PyTorch) and cloud-based AI services.
• US resident.

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