Jan 2026 – Present · 2 mos

Jan 2026 – Present · 2 mos

Jan 2026 – Present · 2 mos

Aug 2025 – Present · 7 mos

Apr 2023 – Present · 2 yrs 11 mos

• Our research focus on AI Memory : "Systems that can accumulate a) context, learn across b) experiences, and build a persistent c) identity over time—enabling true d) agency"

Jan 2023 – Present · 3 yrs 2 mos

Jan 2023 – Present · 3 yrs 2 mos

• “Because scaling intelligence isn’t just about machines — it’s about imagination”
• Vision
• What if scaling compute wasn’t just about hardware but hardware & software?
• Have you ever led a team turning raw silicon into intelligent infrastructure?
• How do you balance innovation, efficiency, & sustainability in large-scale AI systems?
• What if your next decision could multiply a company’s AI capabilities 10x?
• Have you ever transformed complexity into opportunity one node at a time?
• Strategy
• What’s the value of reducing AI training time from weeks to hours?
• How do you turn GPU clusters into competitive advantage?
• Have you ever aligned technical scalability with business growth?
• How do you translate teraflops into business impact?
• What if your infrastructure strategy could reshape product timelines?
• AI Optimization
• Have you ever tuned an AI algorithm that breathes through hundreds of GPUs?
• What happens when you push deep learning beyond the limits of one machine?
• How do you teach an AI to think faster than its data pipeline?
• Can optimization become art when you scale from one GPU to GPU Cluster Fleet?
• Scaling
• Have you ever designed an infrastructure capable of processing petabytes in a single day?
• What if your compute cluster could think faster than your data could move?
• Have you ever built a system where hundreds of GPUs collaborate like a single mind?
• What does it take to connect dozens of GPUs into a unify intelligence?
• Ever wondered how distributed memory behaves when scaling?
• How do you architect a cluster that never sleeps yet learns every second?
• Energy
• What if intelligence could be more efficient?
• How do you design systems that save energy without sacrificing performance?
• What if your GPU clusters could learn smarter & run greener?
• How do you balance performance, precision, and planetary impact?
• What happens when efficiency becomes competitive edge?

Oct 2022 – Present · 3 yrs 5 mos

• Operator & leader in AI, cloud-scale compute, infrastructure, and power management, I drive AI solutions from vision to global impact. I’ve scaled a Netflix-like content platform, delivering innovative products through strategic oversight
• Key Areas of Leadership:
• Entrepreneur Building a Company and Team: Founded an AI-powered content startup, leading AI experts to deliver production-ready apps. Directed hiring and collaboration to accelerate launches and achieve excellence
• Building Something New: Championed AI ecosystems, including a content platform with recommendation engines and real-time processing, scaling to diverse users with resilient web/app experiences.
• Managing a Large Scope and Portfolio of AI Products: Oversaw AI initiatives from research to optimized infrastructure, aligning with business goals and driving hyperscale efficiencies.
• Managing a Team of AI Experts: Led high-performing teams with strategic guidance, collaborating with top researchers to integrate AI breakthroughs, bridging academia and industry.
• Driving Cutting-Edge AI Innovations:
• a) AI Use Cases from Research: Directed transformer model adaptation for content rec., prioritizing rapid deployment.
• b) Build End-User Experiences: Oversaw apps/web products for streaming & monetization, boosting engagement in high-traffic settings.
• c) At Scale Challenges: Led distributed systems to resolve bottlenecks, ensuring 99.9% uptime & cost-effective scaling.
• d) Design Large-Scale AI Compute: Strategized extensible cluster arch. w/ fault-tolerant, energy-efficient designs for cloud-scale AI. I led an XX-node GPU cluster, directing sourcing & optimizing low-latency compute.
• e) Optimization Algorithms: Guided algorithms for resource allocation & power mgmt, enabling ms precision across 1000s of cores.
• f) Building & Scaling AI Agents: Led dev & scaling of AI agents for complex use cases, enhancing automation & decision-making across content & compute platforms.