NoiseNet carries out analysis for our customers - providing automated analysis of audio streams to extract information relevant to our customers. We use a range of analytic, AI, DSP and manual analysis techniques to achieve this.
Due to growing workload, we are seeking to build a small team who are able to assist us with analysis, checking of results, manual listening and tagging of audio samples, and contribution to or preparation of customer reports.
The work will be on a per-hour basis and will be initially intermittent - but will increase over time towards a full-time role. Training will be provided as well as access to all the necessary computational tools. The role will require a very-good and low-cost access to the internet as well as a reasonably capable computer. The majority of analysis will be done on the cloud but at times large files may need to be handled locally.
Initial expectation would be for around 10 hours per week. An initial trial period will apply - and additional hours will be added based on quality and efficiency of work.
The cost of service is also important to us.
We expect that the successful candidate will have experience in audio handling, digital signal processing or acoustics engineering/science and has capability in coding (Python primarily) on a linux platform. Experience with AWS is desirable.
19 freelancers are bidding on average $16/hour for this job
I have done similar works in my college, but it involved archived text rather than audio. the point is that both don't look different and I thus have experience in this type of job.
I have a neutral and fluent English accent. I have a set-up that makes the recording very easy to carry out. x2 Rifle Microphones x1 Zoom H5N interface X1 isolated naturally reverberant space