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Location
Hybrid (Lausanne, Switzerland)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Sep 1, 2026. Logitech scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Logitech is a Swiss company founded in 1981 that makes computer peripherals and has repeatedly found new markets as computing habits changed, moving from mice and keyboards into video collaboration, gaming, streaming and audio. Its gaming brand Logitech G, the streaming hardware business Streamlabs, the audio brands Ultimate Ears and Jaybird, and its video conferencing systems now sit alongside the original peripheral lines. Headquartered in Lausanne and listed in Zurich and on Nasdaq, it sells almost entirely through retail and distribution rather than direct, and its results move with personal computer shipments and hybrid working patterns.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.

The Role and Team:

As an Audio Machine Learning Data Engineer on the Logitech Hardware Audio Machine Learning and DSP Product team, you will work on developing and managing our audio datasets and data pipelines. This work directly influences the innovative audio experiences we deliver to our customers.

Your Contribution:

Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will:

  • Data Pipeline Management: Ensuring the integrity and quality of Audio Machine Learning data pipelines and datasets, which involves robust data augmentation and managing workflows for supervised, unsupervised, and semi-supervised Machine Learning audio applications.

  • Model Development and Deployment: Collaborating with the team to develop and deploy Audio Machine Learning models, specifically targeting platforms with strict resource limitations (such as Tensilica DSP, ARM, and RISC-V).

  • Design and manage audio data collection, curation, labeling, cleaning and augmentation pipelines

  • Evaluate and implement scalable data augmentation techniques.

  • Establish and maintain high-quality, well-versioned, and documented datasets essential for training, validation, and benchmarking of audio Machine Learning models.

  • Build automated tools for monitoring and ensuring the quality and statistical diversity of audio data.

  • Formulate and execute strategies for continuous improvement of existing datasets.

Key Qualifications:

For consideration, you must bring the following minimum skills and experiences to our team:

  • Audio Data Expertise: A minimum of 3 years of direct experience working with extensive audio datasets, including advanced data augmentation and preprocessing techniques audio Machine Learning.

  • Python Proficiency: Strong proficiency in Python for both Machine Learning model development and automating data pipelines.

  • Data Pipelines and Machine Learning Frameworks: Proven expertise in building scalable data pipelines and expertise in employing Machine Learning frameworks (TensorFlow, Keras) with large-scale, complex datasets

Preferred Qualifications:

  • Expert-level skills in audio analysis, including listening and artifact detection, with a proven track record of validating performance across diverse datasets.

  • Strong familiarity with designing, executing, and statistically analyzing audio quality measurement protocols, specializing in managing data-driven objective and subjective evaluations.

  • A strong data-first mindset, with a demonstrated ability to drive innovation both independently and as part of a team.

  • Proficiency in C and SQL, along with experience using code version control systems (Git), is a valuable asset.

  • Excellent cross-functional communication, documentation, and leadership skills, emphasizing transparency in data and results.

Education:

  • Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a related discipline.

  • Equivalent practical experience in professional audio Machine Learning and data engineering considered; advanced/relevant continuing education preferred.

Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.

Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!

We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.

All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.

If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at +1-510-713-4866 for assistance and we will get back to you as soon as possible.

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