Audio Machine Learning Engineer

Cisco Systems; Glasgow; On-site; GBP 40,000 - 70,000; Full time

Job summary

Cisco Systems is seeking a Speech/Audio Machine Learning Engineer for its Audio AI team. This role involves developing innovative audio software solutions leveraging machine learning techniques to enhance audio processing. The candidate will work with a multidisciplinary team, contributing significantly to next-generation audio products.

Benefits

10 days off for community service

Inclusive work environment

Qualifications

• 0+ years of experience with Ph.D. or 3+ years with Masters in ML for audio.
• Proficiency in Python, Matlab, and audio processing libraries.
• Familiarity with deep learning architectures (CNNs, RNNs, GANs).

Responsibilities

• Collaborate on ML models for audio processing and enhancement.
• Train and fine-tune machine learning models.
• Integrate algorithms into audio software products.

Skills

Programming in Python

Programming in Matlab

Machine Learning Techniques

Problem-Solving Skills

Education

Ph.D. in relevant field

Masters in relevant field

Tools

Audio Processing Libraries

PyTorch

Librosa

Job description

Please note this posting is to advertise potential job opportunities. This exact role may not be open today, but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens.
Who are we?

The BabbleLabs team, part of Cisco WebEx. We are a dedicated bunch with strong backgrounds in Electrical Engineering, Machine Learning, Speech Processing and Computer Science. Our areas of expertise include speech enhancement, speech recognition, speech synthesis, and computer vision. But what sets our team apart from the crowd, is our vibrant and unwavering pursuit of excellence

Overview:

We are seeking a dedicated and innovative Machine Learning expert to join our Audio AI team. As a Speech/Audio Machine Learning Engineer, you will play a crucial role in developing pioneering audio software solutions, using machine learning techniques to enhance audio processing and analysis. You will work closely with a multidisciplinary team of engineers, data scientists, and audio experts to build groundbreaking products that push the boundaries of audio technology. This is a unique opportunity to contribute to the development of next-generation audio software and make a significant impact in the industry.

Key Responsibilities:

• Collaborate with cross-functional teams to design and implement machine learning models and algorithms for audio processing, analysis, and enhancement.
• Train, validate, and fine-tune machine learning models for various applications.
• Evaluate and benchmark the performance of machine learning models using appropriate metrics and statistical techniques.
• Collaborate with software engineers to integrate machine learning algorithms into audio software products and ensure seamless functionality and performance.
• Debug and solve issues related to machine learning algorithms and audio software applications.
• Document software development processes, algorithms, and experiments, and communicate findings and recommendations to the team effectively.

Our Minimum Qualifications for this Role:

• Ph.D. in relevant field with 0+ years or Masters in relevant field with 3+ years of experience in developing and deploying machine learning models for audio related applications.
• Must have Strong programming skills in Python and Matlab, with experience in audio processing libraries (e.g., librosa, torch audio, or similar).
• Must understand machine learning techniques, including deep learning architectures (e.g., CNNs, RNNs, GANs) and relevant frameworks (e.g., PyTorch).
• Must be proficiency in data preprocessing, feature extraction, and data augmentation techniques for audio.
• Expected to have strong problem-solving skills and ability to think creatively to devise innovative solutions to audio-related challenges is required.

Our Preferred Qualifications for this Role:

• Familiarity with audio signal processing concepts, such as Fourier analysis, spectral modeling, and time-frequency representations is essential.

Why Cisco?

#WeAreCisco. We are all unique, but collectively we bring our talents to work as a team, to develop innovative technology and power a more inclusive, digital future for everyone. How do we do it? Well, for starters – with people like you!

Nearly every internet connection around the world touches Cisco. We’re the Internet’s optimists. Our technology makes sure the data traveling at light speed across connections does so securely, yet it’s not what we make but what we make happen which marks us out. We’re helping those who work in the health service to connect with patients and each other; schools, colleges, and universities to teach in even the most challenging of times. We’re helping businesses of all shapes and sizes to connect with their employees and customers in new ways, providing people with access to the digital skills they need and connecting the most remote parts of the world – whether through 5G, or otherwise.

We tackle whatever challenges come our way. We have each other’s backs, we recognize our accomplishments, and we grow together. We celebrate and support one another – from big and small things in life to big career moments. And giving back is in our DNA (we get 10 days off each year to do just that).

We know that powering an inclusive future starts with us. Because without diversity and a dedication to equality, there is no moving forward. Our 30 Inclusive Communities, that bring people together around commonalities or passions, are leading the way. Together we’re committed to learning, listening, caring for our communities, whilst supporting the most vulnerable with a collective effort to make this world a better place either with technology, or through our actions.

So, you have colorful hair? Don’t care. Tattoos? Show off your ink. Like polka dots? That’s cool. Pop culture geek? Many of us are. Passion for technology and world changing? Be you, with us! #WeAreCisco

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