Senior Software Machine Learning Engineer (Teradyne, North Reading, MA)

Teradyne•North Reading, MA

3d•$133,900 - $223,900•Onsite

About The Position

Join Teradyne, a global leader in automated test equipment (ATE) and industrial automation. Our technologies power the most advanced semiconductor and electronics testing in the world, enabling manufacturers to bring products to market faster and with greater confidence. As we deepen our AI capabilities, we are looking for exceptional engineers who combine rigorous technical foundations with the drive to take ideas all the way to production. As Senior Machine Learning Engineer, you are Teradyne's highest individual contributor technical authority in ML. You own the end-to-end technical excellence of Teradyne's machine learning systems: from research and experimentation to production deployment and ongoing model performance. You will define modeling standards, set the engineering bar for the entire ML team, and take personal ownership of the most complex and highest-impact ML problems. Your work will span time-series analysis of semiconductor parametric test data, computer vision for defect detection, adaptive test optimization, and applied LLM systems. You will be the go-to technical voice when the team faces hard problems and the mentor of junior engineers around you.

Requirements

5+ 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 & stakeholders.
Computer vision skills in manufacturing inspection: defect detection, etc.

Nice To Haves

ML model deployment on edge devices is preferred, including quantization, ONNX, etc.
Open-source ML project contributions, publications, or technical patents is preferred.
Knowledge of AI agent frameworks (LangChain, AutoGen) or reasoning-driven workflow design (Chain-of-Thought, Chain-of-Action) is preferred.

Responsibilities

Own the technical direction and quality of all ML model development across Teradyne's AI initiatives, setting and enforcing engineering standards across the team.
Lead end-to-end development of production ML systems: data ingestion and feature engineering, model architecture design, training pipelines, evaluation frameworks, and deployment.
Design and implement novel ML approaches tailored to Teradyne's unique data domain including time-series parametric test data (STDF/TEMS), wafer map analysis, etc.
Drive applied research and model innovation, explore and evaluate new architectures, algorithms, and training methodologies, and translate promising approaches into production systems.
Develop and maintain rigorous model evaluation frameworks, including validation methodologies, risk quantification, and production monitoring strategies.
Lead technical design reviews; serve as final arbiter of ML architecture and modeling decisions for the team.
Build and maintain production ML systems with a strong focus on reliability, scalability, and performance in Teradyne's ATE and manufacturing environments.
Partner directly with customers and application engineers to understand real-world debug workflows and translate them into ML solutions.
Mentor and develop junior ML engineers; cultivate a culture of technical rigor and continuous learning.