Machine Learning Engineer, AI Labs

About this role

<div class="content-intro"><h2>Join the Future of Security at Netskope</h2> <p>Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.</p> <p>At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.</p> <p>Visit <a href="https://www.netskope.com/company/careers" target="_blank">Careers at Netskope</a> to learn more. Follow us on <a href="https://www.linkedin.com/company/netskope" target="_blank">LinkedIn</a> and <a href="https://www.instagram.com/netskope/" target="_blank">Instagram</a>.</p></div><h3><strong>About Netskope & AI Labs</strong></h3> <p>Within Netskope Engineering, <strong>Netskope AI Labs</strong> is the powerhouse advancing state-of-the-art artificial intelligence (AI) and machine learning (ML) to protect the modern enterprise. We build the intelligence behind the Netskope Intelligent Security Service Edge (SSE) platform.</p> <p>We are seeking a high-caliber <strong>Machine Learning Engineer</strong> to help us build, optimize, and deploy enterprise-scale AI solutions. Working closely with senior architects, you will directly influence our Secure Access Service Edge (SASE) architecture, turning cutting-edge AI research into production-grade reality.</p> <p><strong>Note on Leveling:</strong> We believe great talent doesn't always fit into a rigid box. Candidates are assessed individually and leveled (from mid to senior) according to their specific skills, background, and technical depth.</p> <h3><strong>🚀 What’s in it for You?</strong></h3> <ul> <li><strong>High-Impact Ownership:</strong> You aren't just maintaining pipelines; you are playing a critical role in the AI transformation of a market-leading cloud security company.</li> <li><strong>Cutting-Edge Stack:</strong> Work on the bleeding edge of LLM inference optimization, utilizing tools like <strong>vLLM, SGLang, and advanced KV Cache optimization</strong>.</li> <li><strong>Elite Collaboration:</strong> Work alongside top-tier engineers, researchers, and ML scientists to solve the industry’s toughest challenges in latency, throughput, and cloud security.</li> </ul> <h3><strong>🛠️ What You Will Do</strong></h3> <ul> <li><strong>Collaborate on the AI Roadmap:</strong> Play a key role alongside senior architects and team members in driving the execution of critical AI/ML technical strategies, building highly scalable, reliable, and production-grade systems.</li> <li><strong>Architect High-Performance Inference Systems:</strong> Design, optimize, and deploy enterprise-scale LLM serving infrastructures. You will push the boundaries of throughput and latency.</li> <li><strong>Own the End-to-End AI Lifecycle:</strong> Partner closely with ML scientists and product stakeholders to translate complex business requirements into elegant, deployed code.</li> <li><strong>Enforce AI Excellence:</strong> Implement and scale strict "Report Cards" for production models, tracking real-world accuracy, latency, and security relevance.</li> </ul> <h3><strong>💡 What You Bring</strong></h3> <ul> <li><strong>Industry Experience:</strong> <strong>10+ years of overall experience in software engineering and product development</strong>, with a specialized focus in one of two tracks:</li> <ul> <li><strong>The AI/ML Focus:</strong> 2+ years of production experience developing, optimizing, and deploying AI/ML solutions (or an equivalent blend of an advanced technical degree + hands-on experience).</li> <li><strong>The Distributed Systems Focus:</strong> 6+ years of deep experience architecting, building, and scaling high-performance distributed systems, combined with a strong desire to apply those infrastructure skills to cutting-edge AI/LLM engineering.</li> </ul> <li><strong>The Modern AI Stack:</strong> Direct exposure to (or a strong conceptual understanding of) optimizing LLMs in production. Familiarity with high-throughput inference frameworks (e.g., <strong>vLLM, SGLang, TensorRT-LLM</strong>) and memory management techniques like <strong>KV Cache optimization</strong> is a massive plus.</li> <li><strong>Clear Communication:</strong> The ability to distill complex technical architecture or infrastructure bottlenecks into clear, actionable concepts for cross-functional teams.</li> <li><strong>The Startup Mindset:</strong> You are an energetic self-starter who thrives in fast-paced,…