Job description

We are the global test and automation specialists, powering next-generation technologies through sophisticated solutions. Behind every electronic device you use, Teradyne's test technology ensures your device works right the first time, every time! Our portfolio of automation solutions help manufacturers to develop and deliver products quickly, efficiently and cost-effectively. Together, Teradyne companies deliver manufacturing automation across industries and applications around the world! We attract, develop, and retain a high-performance workforce, comprised of people with diverse backgrounds and a shared drive for excellence. We strive to foster a positive and inclusive work environment that helps employees, and communities, thrive. Teradyne is a global leader in automated test equipment and industrial automation. Our technologies support advanced semiconductor and electronics testing, helping manufacturers bring products to market faster and with greater confidence. As we deepen our AI capabilities, we’re looking for an engineering leader who combines strong technical judgment with the ability to grow a team. Opportunity Overview As Technical Lead Manager, AI Engineering, you will be the technical authority for one of Teradyne’s AI Product tracks and manage the engineers who deliver it. This is a technical leadership role first: you will set architecture and modeling direction, lead design reviews, and stay close enough to the work to make difficult technical decisions yourself. You will manage a team of approximately five to ten ML engineers, own a defined portion of the multi-year AI product roadmap, and move initiatives from evaluation through benefit realization. You will report to the Head of Machine Learning and partner closely with business unit stakeholders. Key Responsibilities • Set modeling and architecture standards for your track, lead design reviews, and make final technical decisions for your team’s ML systems. • Stay hands-on by prototyping to reduce risk, reviewing data, code, and models, and maintaining a high engineering bar. • Lead initiatives through evaluation, feasibility, development, pilot, and benefit realization; own the associated FTE estimates and delivery commitments. • Hire, coach, and develop ML engineers, including performance management and career growth. • Translate business unit needs into tractable ML problems and explain model behavior in terms stakeholders can act on. • Partner with peer Technical Lead Managers to maintain consistent standards across the AI Product organization. • Own production quality, including monitoring, drift, retraining, and response to model issues in customer environments. • Represent your track in roadmap, resourcing, and executive reviews, including annual FTE and headcount planning. All About You You are an experienced ML practitioner who has taken systems into production and remained accountable for their performance. You can set and defend technical direction with senior stakeholders, make sound trade-offs, and identify work that is unlikely to deliver value. You also enjoy helping engineers grow—whether you have managed a team formally or are a strong technical lead ready to take that step. Required Qualifications • 8+ years of experience in machine learning, applied AI, or a related field, including production ownership of ML systems. • Experience leading engineers through mentoring, technical leadership, or management. • Depth in at least one of the following: time-series and anomaly detection; computer vision for inspection; or applied LLM and agentic systems. • Experience deploying and maintaining ML systems, including MLOps, monitoring, evaluation, and iteration. • Ability to establish technical direction and communicate effectively with customers, business units, and executives. • Master’s or Ph.D. in Computer Science, Electrical Engineering, Statistics, or a related quantitative field—or equivalent industry experience demonstrating technical leadership. Preferred Qualifications • Experience hiring and building an engineering team in a competitive market. • Experience in semiconductor, automated test equipment, or manufacturing environments. Relevant Technical Experience • ML and deep learning: PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn; supervised, self-supervised, and reinforcement learning. • Time-series: Forecasting, prediction, and anomaly detection using high-volume parametric test data, including STDF/TEMS. • MLOps: MLflow, Weights & Biases, Hugging Face, model registries, ML CI/CD, and production monitoring. • Data engineering and infrastructure: Spark, Pandas, SQL, Docker, Kubernetes, Azure ML, and GCP Vertex AI. • LLMs: Fine-tuning (SFT, RLHF, DPO), prompt engineering, evaluation frameworks, and agentic workflow design. Compensation: The base salary range for this role is $199,600-$319,300. This range is a good faith estimate, and the amount of base salary will correspond with experience and skill set. This range can also fluctuate depending on demand and location. Incentive Plan: This job is eligible for discretionary bonus(es) based on financial performance. Benefits: Teradyne offers a variety of robust health and well-being benefit programs, including medical, dental, vision, Flexible Spending Accounts, retirement savings plans, life and disability insurance, paid vacation & holidays, tuition assistance programs, and more.  Please click here to see details.

Requirements

Must-haves

Opportunity Overview
Set modeling and architecture standards for your track, lead design reviews, and make final technical decisions for your team’s ML systems.
Stay hands-on by prototyping to reduce risk, reviewing data, code, and models, and maintaining a high engineering bar.
Lead initiatives through evaluation, feasibility, development, pilot, and benefit realization; own the associated FTE estimates and delivery commitments.
Hire, coach, and develop ML engineers, including performance management and career growth.
Translate business unit needs into tractable ML problems and explain model behavior in terms stakeholders can act on.
Partner with peer Technical Lead Managers to maintain consistent standards across the AI Product organization.
Own production quality, including monitoring, drift, retraining, and response to model issues in customer environments.
Represent your track in roadmap, resourcing, and executive reviews, including annual FTE and headcount planning.
All About You
8+ years of experience in machine learning, applied AI, or a related field, including production ownership of ML systems.
Experience leading engineers through mentoring, technical leadership, or management.
Depth in at least one of the following: time-series and anomaly detection; computer vision for inspection; or applied LLM and agentic systems.
Experience deploying and maintaining ML systems, including MLOps, monitoring, evaluation, and iteration.
Ability to establish technical direction and communicate effectively with customers, business units, and executives.

Nice-to-haves

Experience hiring and building an engineering team in a competitive market.
Experience in semiconductor, automated test equipment, or manufacturing environments.
Relevant Technical Experience
ML and deep learning: PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn; supervised, self-supervised, and reinforcement learning.
Time-series: Forecasting, prediction, and anomaly detection using high-volume parametric test data, including STDF/TEMS.
MLOps: MLflow, Weights & Biases, Hugging Face, model registries, ML CI/CD, and production monitoring.
Data engineering and infrastructure: Spark, Pandas, SQL, Docker, Kubernetes, Azure ML, and GCP Vertex AI.
LLMs: Fine-tuning (SFT, RLHF, DPO), prompt engineering, evaluation frameworks, and agentic workflow design.
Incentive Plan: This job is eligible for discretionary bonus(es) based on financial performance.

Application prep

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Keywords to mirror

aimlmachine learningllmci/cdsqldockerkubernetesazuregcp

Platform: successfactors
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision