Principal Machine Learning Engineer - job 1 of 2

To be considered for the Principal Machine Learning Engineer role at Zscaler, candidates should possess a Bachelor's degree in Computer Science, Mathematics, or a related field, with a Master's or PhD preferred. Additionally, candidates must have at least 10 years of industry or academic experience in machine learning, statistical modeling, or applied AI. Proficiency in Python, SQL, and various ML libraries and frameworks is essential, alongside hands-on experience with cloud-based AI platforms such as AWS SageMaker or GCP Vertex AI.

As a Principal Machine Learning Engineer at Zscaler, your main responsibilities will include designing and optimizing AI/ML models and pipelines, leading the development of scalable AI solutions, and providing technical guidance to junior engineers. You will also architect AI platforms for distributed training and real-time inference, build AI/ML model orchestration pipelines using Kubernetes, and collaborate with cross-functional teams to align AI initiatives with business objectives.

To stand out for the Principal Machine Learning Engineer role at Zscaler, it’s beneficial to have a proven track record of designing, building, and shipping large-scale AI-driven applications. Experience with LLM architectures, agent frameworks, and state-of-the-art AI technologies will be a significant asset. Additionally, familiarity with cybersecurity SaaS products or contributions to open-source AI/ML projects will make your application even more compelling.

Zscaler promotes a fast-paced, collaborative work culture that values inclusivity and innovation. As a Principal Machine Learning Engineer, you will be surrounded by bright minds and experienced professionals who are passionate about their work. The company is committed to creating a supportive environment where diversity drives creativity, and employees are encouraged to bring their unique perspectives to the table.

The salary range for the Principal Machine Learning Engineer position at Zscaler is competitive, ranging from $175,000 to $250,000 USD, depending on various factors including experience and qualifications. This base pay excludes commission, bonus, or equity, and Zscaler also offers comprehensive benefits to support employees throughout their life stages.

When answering this question, provide examples of specific ML frameworks you have worked with, highlighting your proficiency and any projects where you successfully applied these tools in real-world scenarios. Mention your experience in optimizing models and pipelines, which is crucial for the role at Zscaler.

During your response, discuss any significant projects where you led the design and implementation of AI-driven applications. Focus on the technologies used and the business outcomes achieved to showcase your direct impact on product success.

Your answer should touch on the specific methodologies you utilize when architecting these platforms. Share your experiences with distributed training and emphasize your understanding of observability, which is important in monitoring AI systems effectively.

Here, highlight your communication skills and techniques for breaking down complex ideas. Discuss past experiences where you successfully conveyed challenging concepts to non-technical stakeholders to ensure alignment and understanding.

Provide specific examples of how you've used Docker and Kubernetes in machine learning projects, including any challenges faced and how you overcame them. This will demonstrate your hands-on experience, which is valued at Zscaler.

Address your mentoring philosophy by discussing how you guide and support junior engineers. Share instances where you enhanced their skills or contributed to their career growth, as mentorship is a valued aspect of the role.

Discuss your familiarity with MLOps tools and practices, including your understanding of model orchestration and deployment processes. Acknowledge how this experience helps streamline ML projects at Zscaler.

When discussing trends, focus on new developments in AI/ML, such as advancements in large language models or specific AI technologies that intrigue you. Your passion for innovation can resonate with Zscaler's culture.

Here, elaborate on the importance of security in AI applications, especially in a cybersecurity context. Share best practices you've implemented to secure ML systems and any relevant experience you have in cybersecurity.

Your answer should reflect your alignment with Zscaler's mission and values. Speak about your passion for cloud security and how being part of a forward-thinking company excites you, portraying your enthusiasm for the role.