Ai/ml Technologist

Intel Intel · Semiconductors · Bangalore, India

Seeking an experienced AI/ML Technologist to lead the transformation of client platform technologies, debug, and power/performance domains using advanced AI tools and machine learning techniques. This role will drive innovation by leveraging cutting-edge Agentic AI architectures to enhance efficiency, scalability, and intelligence across client product development, debugging, and power-performance optimization workflows.

What you'd actually do

  1. Define and implement scalable AI/ML architectures to modernize platform technologies, debug, and power/performance workflows.
  2. Design and develop intelligent, autonomous agents capable of self-orchestrating debugging, analysis, and optimization tasks, enabling continuous learning and decision-making.
  3. Power and Performance Analytics: Develop advanced analytics frameworks to monitor, predict, and optimize power efficiency and system performance metrics for client products.
  4. Data-Driven Insights: Leverage ML models and telemetry data to deliver actionable insights for system-level optimization, anomaly detection, and performance bottleneck analysis.
  5. Cross-Functional Collaboration: Partner with hardware, software, and platform engineering teams to integrate AI-driven solutions into existing ecosystems.

Skills

Required

  • Machine Learning
  • Deep Learning
  • AI system design
  • Agentic AI / autonomous systems / multi-agent frameworks
  • platform technologies
  • system debug
  • power/performance optimization workflows
  • data analytics
  • performance modeling
  • optimization techniques
  • cloud platforms
  • distributed systems
  • scalable pipelines
  • MLOps
  • production deployment of AI systems
  • reinforcement learning
  • decision systems
  • adaptive agents
  • Python
  • C/C++
  • Power Shell scripting

Nice to have

  • Memory, CPU, GPU, and system architecture
  • Debugging at system/software/hardware interaction level

What the JD emphasized

  • Agentic AI architectures
  • intelligent, autonomous agents
  • self-orchestrating debugging
  • system-level optimization
  • AI-driven solutions

Other signals

  • Leveraging cutting-edge Agentic AI architectures
  • Design and develop intelligent, autonomous agents
  • integrate AI-driven solutions into existing ecosystems