[AUDITORY] Open position at Gracenote / Audio Research Engineer (Machine Learning) / Emeryville, CA, USA (Zafar Rafii )


Subject: [AUDITORY] Open position at Gracenote / Audio Research Engineer (Machine Learning) / Emeryville, CA, USA
From:    Zafar Rafii  <zafarrafii@xxxxxxxx>
Date:    Fri, 8 Jun 2018 16:39:47 -0700
List-Archive:<http://lists.mcgill.ca/scripts/wa.exe?LIST=AUDITORY>

--000000000000fc7e77056e29ea3d Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable (apologies for cross-posting) Hi all, Gracenote (http://www.gracenote.com/) is looking for an audio research engineer with experience in machine learning to join the applied research group in Emeryville, CA, USA. Details can be found below and candidates can apply here: https://jobs.nielsen.com/job/Emeryville-Audio-Research-Engineer-CA-94608/47= 9953500/?locale=3Den_US Thank you, Zafar Gracenote is an entertainment data and technology provider powering the world=E2=80=99s top music services, automakers, cable and satellite operato= rs, and consumer electronics companies. At its core, Gracenote helps people find, discover and connect with the entertainment they love. Daily, Gracenote processes 35 billion pieces of data and is quickly becoming a world-leader in return path =E2=80=9Cbig data.=E2=80=9D Over the past 3 years, the compa= ny has grown to more than 2000 employees in 17 countries, including over 600 of the world= =E2=80=99s top engineers with a passion for music, video, sports, and entertainment technology. Founded in 1998, Gracenote is one of America=E2=80=99s most ico= nic and respected media companies. We are presently looking for an Audio Research Engineer to join the Applied Research team at Gracenote. This team develops cutting edge technologies relating to music and audio, including media recognition, machine listening, data processing pipelines, and recommendation systems. In your role on the team, you will help develop and disseminate these technologies throughout the company and to customers by developing algorithms and tools, creating demo applications, and writing production system components. Applicants should include a cover letter. FOR THIS ROLE WE ARE LOOKING FOR INDIVIDUALS THAT HAVE: - Practical and theoretical experience with machine learning and digital signal processing - Experience with neural network based data classification - Good programming skills in Python, C/C++, and Matlab - Interested in working on an ever-changing list of audio related projects - Enthusiastic about audio, music, music data, and solving problems in this space - Self starter capable of working independently and across a variety of engineering teams - Masters or PhD in Computer Science, EE, or a related field preferred DESIRABLE: - 2+ years of professional experience in neural network based machine learning with audio - Experience with accelerated machine learning tools such as Tensorflow, Keras, Theano, etc. - Cross platform experience - Linux, Windows, OS X - Versatile candidates with experience in a variety of other languages such as Swift, Objective C, Java, JavaScript, Scala, etc. - Familiarity with music and music technologies (e.g. MIDI, music theory) - Bash and shell scripting experience - Experience handling large amounts of data and familiarity with databases - Experience developing end to end project workflow in Machine learning systems - literature review, data collection, building ML system infrastructure, evaluation systems, and productionizing / integration into services - Experience building native applications for Mac, Windows, iOS, and Androi= d - Experience with cloud services such as AWS or Google Cloud - Experience setting up cloud systems involving the Apache technology stack Our passion for music, TV, movies, and sports is at the heart of everything we do. But what really makes us tick is our people. From Emeryville to Sydney and Queensbury to Amsterdam, we are building the team that=E2=80=99s= going to disrupt the digital universe. This starts by creating a workplace where all things entertainment are celebrated and innovation can come from anyone. If you are interested in being mission critical and on the leading edge of global entertainment technology then please contact us today! #LI-GN Gracenote, a Nielsen company, is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. --000000000000fc7e77056e29ea3d Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr"><div>(apologies for cross-posting)</div><div><br></div><di= v>Hi all,</div><div><br></div><div>Gracenote (<a href=3D"http://www.graceno= te.com/">http://www.gracenote.com/</a>) is looking for an audio research en= gineer with experience in machine learning to join the applied research gro= up in Emeryville, CA, USA. Details can be found below and candidates can ap= ply here: <a href=3D"https://jobs.nielsen.com/job/Emeryville-Audio-Research= -Engineer-CA-94608/479953500/?locale=3Den_US">https://jobs.nielsen.com/job/= Emeryville-Audio-Research-Engineer-CA-94608/479953500/?locale=3Den_US</a></= div><div><br></div><div>Thank you,</div><div><br></div><div>Zafar</div><div= ><br></div><div><br></div><div><br></div><div>Gracenote is an entertainment= data and technology provider powering the world=E2=80=99s top music servic= es, automakers, cable and satellite operators, and consumer electronics com= panies. At its core, Gracenote helps people find, discover and connect with= the entertainment they love. Daily, Gracenote processes 35 billion pieces = of data and is quickly becoming a world-leader in return path =E2=80=9Cbig = data.=E2=80=9D Over the past 3 years, the company has grown to more than 20= 00 employees in 17 countries, including over 600 of the world=E2=80=99s top= engineers with a passion for music, video, sports, and entertainment techn= ology. Founded in 1998, Gracenote is one of America=E2=80=99s most iconic a= nd respected media companies.=C2=A0</div><div><br></div><div>We are present= ly looking for an Audio Research Engineer to join the Applied Research team= at Gracenote. This team develops cutting edge technologies relating to mus= ic and audio, including media recognition, machine listening, data processi= ng pipelines, and recommendation systems. In your role on the team, you wil= l help develop and disseminate these technologies throughout the company an= d to customers by developing algorithms and tools, creating demo applicatio= ns, and writing production system components.</div><div><br></div><div>Appl= icants should include a cover letter.</div><div><br></div><div>FOR THIS ROL= E WE ARE LOOKING FOR INDIVIDUALS THAT HAVE:</div><div><br></div><div>- Prac= tical and theoretical experience with machine learning and digital signal p= rocessing</div><div>- Experience with neural network based data classificat= ion</div><div>- Good programming skills in Python, C/C++, and Matlab</div><= div>- Interested in working on an ever-changing list of audio related proje= cts</div><div>- Enthusiastic about audio, music, music data, and solving pr= oblems in this space</div><div>- Self starter capable of working independen= tly and across a variety of engineering teams</div><div>- Masters or PhD in= Computer Science, EE, or a related field preferred</div><div>=C2=A0</div><= div><br></div><div>DESIRABLE:</div><div><br></div><div>- 2+ years of profes= sional experience in neural network based machine learning with audio</div>= <div>- Experience with accelerated machine learning tools such as Tensorflo= w, Keras, Theano, etc.</div><div>- Cross platform experience - Linux, Windo= ws, OS X</div><div>- Versatile candidates with experience in a variety of o= ther languages such as Swift, Objective C, Java, JavaScript, Scala, etc.</d= iv><div>- Familiarity with music and music technologies (e.g. MIDI, music t= heory)</div><div>- Bash and shell scripting experience</div><div>- Experien= ce handling large amounts of data and familiarity with databases</div><div>= - Experience developing end to end project workflow in Machine learning sys= tems - literature review, data collection, building ML system infrastructur= e, evaluation systems, and productionizing / integration into services</div= ><div>- Experience building native applications for Mac, Windows, iOS, and = Android</div><div>- Experience with cloud services such as AWS or Google Cl= oud</div><div>- Experience setting up cloud systems involving the Apache te= chnology stack</div><div><br></div><div>Our passion for music, TV, movies, = and sports is at the heart of everything we do. But what really makes us ti= ck is our people. From Emeryville to Sydney and Queensbury to Amsterdam, we= are building the team that=E2=80=99s going to disrupt the digital universe= . This starts by creating a workplace where all things entertainment are ce= lebrated and innovation can come from anyone. If you are interested in bein= g mission critical and on the leading edge of global entertainment technolo= gy then please contact us today!</div><div><br></div><div>#LI-GN</div><div>= <br></div><div>Gracenote, a Nielsen company, is committed to hiring and ret= aining a diverse workforce. We are proud to be an Equal Opportunity/Affirma= tive Action-Employer, making decisions without regard to race, color, relig= ion, gender, gender identity or expression, sexual orientation, national or= igin, genetics, disability status, age, marital status, protected veteran s= tatus or any other protected class.</div><div><br></div></div> --000000000000fc7e77056e29ea3d--


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