The world’s best audio processing software.

Applying over 100 years of combined Digital Signal Processing and Machine/Deep Learning experience to deliver better online calls and meetings to billions of daily active users.

Synthetic Media Processing Laboratory

With people learning and working online from all around the globe, they need audio that automatically adapts to networks, devices, and challenging acoustic environments.

We are building the tech that powers great sounding audio. SMPL innovates in the space between traditional signal processing and deep neural networks. By combining our experience with advances in machine learning we are delivering more efficient codecs, better echo cancellation, background noise reduction, packet loss concealment and device management - for the best conversations on the planet.

Working at SMPL

SMPL is a Singapore based company. We work fully remote and are hiring full time employees across any of 150 countries with full compliance and benefits. We offer competitive perks and early stage equity. Come join us!

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Audio & Codec Specialists

You will be building audio software with the inventor/author of virtually all the codecs currently in use on the internet. Your work here will be used by millions, perhaps billions of people daily. We are looking for people with solid signal processing skills who are happy to dive into low level C.

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Neural Network Specialists

The intersection of traditional signal processing and machine learning is the space we are exploiting. Do you have a good understanding of, and hands-on experience with, state of the art audio processing, machine learning, and deep neural networks?

Co-Founders

Koen

Koen Vos

Chief Scientist
Inventor of iSac, SILK, OPUS, Satin

The audio/voice processing algorithms I created power many of today's internet communications platforms. For example, I was the lead developer of Google's iSAC, Skype's SILK and Microsoft's Satin codecs, and co-authored the Opus standard. I have developed from scratch, a broad range of machine/deep learning algorithms for audio processing and financial modeling. I also authored or co-authored around 100 patents related to audio processing and machine learning.

Jon

Jonathan Christensen

General Manager
Microsoft, Skype, Wire, Camino...

I have 20+ years of experience in enterprise and consumer software and services. I have been a successful executive and founder, building and running messaging, voice, video collaboration businesses for startups and big companies. Together with Koen and others I founded both Camino Networks (Sold to Skype) and Wire (ongoing). Although my experience is broad - leading Platform, Partnerships, Sales, Engineering, Product, UX Design, Scientific Research, and Marketing - my core passion is building.

Leads

This team has written more than 250 audio and video related patents and developed commercial products that are used globally by billions of users every day. Please reach out to us if you want to contribute to our mission or if you have questions about SMPL products and services.

 

Karsten

Karsten Vandborg Sørensen, Ph.D.

Principal Audio Engineer
Camino Networks, Skype, Microsoft

As a former tech lead for voice quality enhancement at Microsoft, and principal engineer in the audio team at Skype, I have co-developed and been responsible for the echo cancellation, noise reduction, automatic gain controls (and a lot more) in Teams and Skype. I have also worked with Koen and others on the Silk, Opus, and Satin codecs, and I have authored or co-authored around 30 patents related to audio signal processing.

Henrik

Henrik Astrom

Principal Audio Engineer
Global IP Sound, Camino Networks, Skype, Microsoft

For the last 20+ years I have developed audio signal processing algorithms specifically designed for communication over the Internet. In the early days I was the lead developer of the NetEq jitter buffer, now part of WebRTC. At Skype and Microsoft I lead the over-all research, development and platform porting of the audio pipeline and audio DSP components. My motto was, and still is, to get high fidelity in an optimized and maintainable fashion on all supported platforms - desktop, tablets, mobile phones and embedded systems.

Phil

Phil Hetherington, Ph.D.

Principal DSP Engineer
McGill, UBC, Wavemakers, Harman, QNX, Blackberry, Amazon

I have 30+ years in neural networks and DSP in industries including neuroscience, pro audio, automotive, cell phones, tablets, smart speakers, and TVs. I've written audio DSP algorithms used in millions of phones and over 150M cars worldwide. At Amazon I guided audio and video call quality improvements for Alexa and Fire TV teams. I've published 16 scientific papers and have 114 issued US patents. I'm excited to innovate and drive the next generation of audio communications with the amazing team at SMPL.

Søren

Søren Skak Jensen

Principal Audio Engineer
Microsoft, Wire, Skype, Camino Networks

I am a software engineer with 15 years of experience designing audio DSP algorithms and building commercial software products. I specialize in speech and audio signal processing for interactive, real-time communications over packet-based networks (VoIP). I have co-authored patents related to speech coding, jitter buffering, and packet loss concealment.

Shree

Shree Paranjpe

Principal DSP Engineer
Kurzweil Music Systems, Harman, QNX, Blackberry

In my 28 years of experience, I have researched, patented, and delivered various technologies such as custom silicon DSP architectures, embedded software, and algorithms in products that include professional music synthesizers, audio effects processors, and handsfree systems used in cars, tablets, cell phones, and desktops. I enjoy building audio experiences that will make you smile.

Nicholas

Nicholas Lenz

Machine Learning Intern
UCLA, Duke, Neurolutions

I am a young engineer completing his M.Eng. at Duke University in Electrical Engineering, interested in the intersection of machine learning and audio signal processing. I previously worked at Neurolutions Inc., where I developed algorithms for their real-time EEG system. I have had additional internships in bioinformatics, remote sensing, and controls.

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