Machine Learning Engineering Manager (Teradyne, North Reading, MA)
$199,600 - $319,300 USD yearly
Originally posted 2 October 2026 by the employer.
About the role
This role involves technical leadership and management of an AI Product track, delivering solutions as a Machine Learning Engineering Manager.
What you'll do
- Set modeling and architecture standards, leading design reviews and making technical decisions for ML systems.
- Prototype to reduce risk, review data, code, and models, and maintain a high engineering bar.
- Lead initiatives through evaluation, feasibility, development, pilot, and benefit realization.
- Hire, coach, and develop ML engineers.
- Translate business unit needs into tractable ML problems and explain model behavior to stakeholders.
- Own production quality, including monitoring, drift, retraining, and response to model issues.
What you'll need
- 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.
Nice to have
- Experience hiring and building an engineering team.
- Experience in semiconductor, automated test equipment, or manufacturing environments.
- 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.
Skills: machine learning, AI engineering, ML systems, production ownership, time-series, anomaly detection
This role has been open 0 days — well below the 74-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
509
|
Median days open
74 d
|
Median salary
$225k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Teradyne | All employers we track in this specialty (509 roles · 76 employers) |
|---|---|---|
| Open roles in this specialty | 3 | 509 |
| Open roles in the wider Software, Firmware & Systems family | 95 | 5917 · 145 employers |
| Median days open | 137 d | 74 d (+63 d vs this employer) |
| Median salary (USD postings) | — | $225k |
Skills observed across this category: machine learning, AI engineering, ML systems, production ownership, time-series, anomaly detection
Who's hiring in this category
- Qualcomm · 105 open roles · median 106 d
- NVIDIA · 84 open roles · median 73 d
- AMD · 43 open roles · median 66 d
- Micron Technology · 30 open roles · median 55 d
- Mobileye · 20 open roles · median 70 d
- NXP Semiconductors · 15 open roles · median 60 d
How we counted: 509 open AI/ML Hardware Engineering (AI ML Hardware) roles from 76 employers tracked in the SemiconductorJobs index, counted 3 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.