Data Engineer Audio Anomaly Detection in Fusemachines

Closed job - No longer receiving applicants

Fusemachines is a leading AI strategy, talent, and education services, provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic and more than 250 full-time employees) Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

Job functions

About the role:

This is a full-time position (contract)

Job Description:

There is an exisiting Python application which performs analysis on 15-minute long audio files for the purpose of detecting anomalies such as extended periods of silence, two sound tracks playing at once, popping or cracking noises, etc. This code will be maintained and enhanced by the Data Scientist on the project. The code will provide a function which takes an S3 file key as input, and it will return a JSON (format TBD) payload indicating the presence or absence of any audio anomalies.

Qualifications and requirements

Technical skills
Python
Python REST calls
AWS (Lambda, S3, IAM, Cloudwatch, DynamboDB)
Terraform is a Must

Likely Duration

3-6 months. It is likely the audio detection part of the application will undergo multiple revisions following stakeholder feedback.

Conditions

Fully remote You can work from anywhere in the world.
Pet-friendly Pets are welcome at the premises.
Informal dress code No dress code is enforced.

Remote work policy

Fully remote

Candidates can reside anywhere in the world.

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