Machine Learning Intern - KWS/AED - Redwood City, California, United States
Originally posted 8 September 2026 by the employer — open 2 days.
This role focuses on keyword spotting (KWS) and audio event detection (AED) models.
About the role
This Machine Learning Intern role supports the Algorithms team in developing, evaluating, and improving deep learning models for keyword spotting (KWS) and audio event detection (AED) deployed on ultra-low-power edge hardware. These models run directly on Syntiant's NDP-class neural decision processors.
What you'll do
- Support development and evaluation of KWS and AED models, including single-stage and cascaded detection architectures.
- Assist with audio pipeline and feature extraction work, including filterbank design, log-mel and PCEN-based frontends.
- Help design and prune CNN architectures to fit hardware constraints (fixed input shapes, 8-bit quantization, limited parameter budgets, restricted op sets).
- Build and run false-accept (FA) diagnostic tooling, including categorized probe sets, confusion analysis, and visualization.
- Contribute to hard-negative mining and data augmentation strategies to reduce false accepts.
- Analyze model run results across experiment variants and summarize findings for the team.
What you'll need
- Pursuing or completed a Bachelor's or Master's degree in Computer Science, Electrical Engineering, Machine Learning, or a related field.
- Hands-on experience in deep learning for audio or speech (CNNs/RNNs on spectrogram or time-series audio data).
- Proficiency in Python and a deep learning framework (TensorFlow/Keras preferred; PyTorch acceptable).
- Familiarity with audio signal processing fundamentals (spectrograms, mel filterbanks, feature extraction).
- Understanding of standard ML evaluation concepts (precision/recall trade-offs, ROC/DET curves, confusion analysis).
Nice to have
- Exposure to model efficiency concepts (quantization, parameter budgets, edge/embedded ML constraints).
- Prior internship, research, or personal project experience in audio ML, KWS, or acoustic event detection.
Skills: KWS, AED models, CNN architectures, 8-bit quantization, audio pipeline, TensorFlow
This role has been open 1 day — well below the 63-day median for AI/ML Hardware Engineering roles.
AI/ML Hardware Engineering · AI ML Hardware
|
Open roles in category
508
|
Median days open
63 d
|
Median salary
$224k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Syntiant | All employers we track in this specialty (508 roles · 79 employers) |
|---|---|---|
| Open roles in this specialty | 1 | 508 |
| Open roles in the wider Software, Firmware & Systems family | 4 | 5650 · 142 employers |
| Median days open | 1 d | 63 d (−62 d vs this employer) |
| Median salary (USD postings) | — | $224k |
Skills observed across this category: KWS, AED models, CNN architectures, 8-bit quantization, audio pipeline, TensorFlow
Who's hiring in this category
- Qualcomm · 107 open roles · median 98 d
- NVIDIA · 88 open roles · median 60 d
- AMD · 44 open roles · median 63 d
- Micron Technology · 27 open roles · median 47 d
- Mobileye · 21 open roles · median 44 d
- NXP Semiconductors · 11 open roles · median 64 d
How we counted: 508 open AI/ML Hardware Engineering (AI ML Hardware) roles from 79 employers tracked in the SemiconductorJobs index, counted 10 Sept 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.