Head Of World Models Universal Robots India

Our Purpose

TERADYNE – Join Teradyne, a leader in providing advanced testing and automation solutions, and contribute to the seamless functionality of electronic devices worldwide. Our automation technologies aid manufacturers in enhancing product development and market delivery efficiently. We invite you to be a part of our team, bringing innovation to diverse industries globally

Opportunity Overview

At Teradyne, we are advancing intelligent automation and AI-driven software systems to support engineering workflows. As a Senior Machine Learning Engineer, you will lead the design, development, and deployment of applied AI systems, including large language models (LLMs), reinforcement learning (RL), and intelligent agent workflows. You will serve as technical lead for AI initiatives that integrate deeply with test platforms and engineering environments.

This role requires strong ownership, architectural leadership, and the ability to work directly with customers and internal stakeholders to translate real-world debug challenges into scalable AI solutions. You will collaborate across ML, software, product, and application engineering teams to deliver production-grade AI capabilities.

Key Responsibilities

• Lead end-to-end development of AI systems, including SFT, reward modeling, and RL fine-tuning. Develop reward models and policy optimization frameworks (e.g., PPO, DPO).
• Architect reasoning-driven (CoT) and action-oriented (CoA) AI workflows.
• Design and implement model training pipelines, evaluation frameworks, and deployment strategies.
• Partner directly with customers to understand debug workflows and translate them into AI use cases.
• Drive integration of AI systems into engineering platforms.
• Establish evaluation metrics, validation methodologies, and risk mitigation strategies.
• Mentor junior engineers and interns.
• Contribute to long-term AI capability roadmap and technical strategy.Qualifications:
• Strong analytical and problem-solving skills.
• Proficiency in Python and deep learning frameworks (e.g., PyTorch or TensorFlow).
• Familiarity with large language models and modern AI development tools.
• Experience with AI orchestration or agent frameworks (e.g., LangChain, AutoGen, etc.).
  
  

• Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field (or equivalent industry experience).
• 7+ years of experience in machine learning, applied AI, or related fields.
• Hands-on experience fine-tuning large language models.
• Experience with reinforcement learning (e.g., policy gradients, PPO, actor-critic methods).
• Experience designing reward models or evaluation systems.
• Strong software engineering skills (Python, distributed systems familiarity).
• Experience building production ML systems (MLOps, monitoring, deployment).
• Ability to work cross-functionally with product, software, and hardware teams.
• Strong communication skills; comfortable engaging directly with customers and stakeholders.