Senior Audio ML Engineer — Acoustic Event Detection

Squarehead Technology; Oslo; Hybrid; NOK 900,000 - 1,200,000; Full time

Benefits offered by this job

Conference and courses

Subsidised canteen

Subsidised sports activities

Rooftop terrace

Bike and car parking

Shower facilities

Job summary

Squarehead Technology in Oslo seeks a Senior ML Engineer to develop and train models for detecting acoustic events, including drones, using real-world audio data from advanced sensors. You will join a multidisciplinary team of scientists in signal processing, array technology, and data science in a collaborative R&D environment.

The role emphasizes building robust audio AI systems, evaluating performance under challenging acoustics, and contributing to deployment in real-world systems with

Qualifications

• Advanced degree in ML or related field.
• Experience training and evaluating ML models.
• Strong Python programming with ML frameworks.
• Good understanding of classification and detection.
• Ability to work independently and in multidisciplinary teams.
• Strong analytical and problem solving.

Responsibilities

• Curate and maintain high-quality audio datasets for ML.
• Train and evaluate ML models for audio event detection.
• Analyze model performance and robustness under acoustics.
• Collaborate with signal processing, acoustics, and data science teams.
• Support data labeling, validation, and experimental design.
• Research ML methods for audio and acoustic data.

Skills

Python programming

ML model training

Analytical skills

Independent work

English fluency

Education

MSc or PhD in ML/CS/Signal Processing

Tools

PyTorch

TensorFlow

Job description

Squarehead Technology in Oslo seeks a Senior ML Engineer to develop and train models for detecting acoustic events, including drones, using real-world audio data from advanced sensors. You will join a multidisciplinary team of scientists in signal processing, array technology, and data science in a collaborative R&D environment.

The role emphasizes building robust audio AI systems, evaluating performance under challenging acoustics, and contributing to deployment in real-world systems with