Jobs · greenhouse:netskope
Machine Learning Engineer, AI Labs
Cobalt Streamworks · Taipei, Taiwan · Posted 1d ago
Available in 4 locations
Santa Clara Apply → Santa Clara, California, United States · onsite Apply → Taipei Apply → Taipei, Taiwan · onsite Apply →About the role
About Cobalt Streamworks Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Cobalt Streamworks to redefine Cloud, Network and Data Security. Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Cobalt Streamworks (AWON), we strive to keep work fun, supportive and interactive. Visit us at Cobalt Streamworks Careers. Please follow us on LinkedIn and Twitter @Cobalt Streamworks . About Cobalt Streamworks & AI Labs Within Cobalt Streamworks Engineering, Cobalt Streamworks AI Labs 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 Cobalt Streamworks Intelligent Security Service Edge (SSE) platform. We are seeking a high-caliber Machine Learning Engineer 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. Note on Leveling: 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. 🚀 What’s in it for You? High-Impact Ownership: You aren't just maintaining pipelines; you are playing a critical role in the AI transformation of a market-leading cloud security company. Cutting-Edge Stack: Work on the bleeding edge of LLM inference optimization, utilizing tools like vLLM, SGLang, and advanced KV Cache optimization . Elite Collaboration: Work alongside top-tier engineers, researchers, and ML scientists to solve the industry’s toughest challenges in latency, throughput, and cloud security. 🛠️ What You Will Do Collaborate on the AI Roadmap: 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. Architect High-Performance Inference Systems: Design, optimize, and deploy enterprise-scale LLM serving infrastructures. You will push the boundaries of throughput and latency. Own the End-to-End AI Lifecycle: Partner closely with ML scientists and product stakeholders to translate complex business requirements into elegant, deployed code. Enforce AI Excellence: Implement and scale strict "Report Cards" for production models, tracking real-world accuracy, latency, and security relevance. 💡 What You Bring Industry Experience: 10+ years of overall experience in software engineering and product development , with a specialized focus in one of two tracks: The AI/ML Focus: 2+ years of production experience developing, optimizing, and deploying AI/ML solutions (or an equivalent blend of an advanced technical degree + hands-on experience). The Distributed Systems Focus: 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. The Modern AI Stack: Direct exposure to (or a strong conceptual understanding of) optimizing LLMs in production. Familiarity with high-throughput inference frameworks (e.g., vLLM, SGLang, TensorRT-LLM ) and memory management techniques like KV Cache optimization is a massive plus. Clear Communication: The ability to distill complex technical architecture or infrastructure bottlenecks into clear, actionable concepts for cross-functional teams. The Startup Mindset: You are an energetic self-starter who thrives in fast-paced, dynamic environments and isn't afraid to wear multiple hats to get a product across the finish line. Education BSCS or equivalent required, MSCS or equivalent strongly preferred. #LI-SC3 Cobalt Streamworks is committed to implementing equal employment opportunities for all employees and applicants for employment. Cobalt Streamworks does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate. Cobalt Streamworks respects your privacy and is committed to protecting the personal information you share with us, please refer to Cobalt Streamworks's Privacy Policy for more details. The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Cobalt Streamworks Careers site.
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FAQ
Is the Machine Learning Engineer, AI Labs role at Cobalt Streamworks remote?+
This Machine Learning Engineer, AI Labs position is listed as onsite (Taipei, Taiwan).
What seniority level is this Machine Learning Engineer, AI Labs role?+
This is a unknown level position.
How do I apply for the Machine Learning Engineer, AI Labs role at Cobalt Streamworks?+
Use the "Apply on greenhouse:netskope" button to open the original posting on greenhouse:netskope, where you can submit your application directly to Cobalt Streamworks.