Research Intern – AI-Based Audio Optimization (February 2027)

Keenfinity; Eindhoven; Hybride; EUR 5 600 - 6 700; Temps partiel

Avantages offerts par ce poste

Option to work from home one day per‑w

Internship allowance €500–€600 per mês

Close guidance from experienced pros

Résumé du poste

Keenfinity in Eindhoven is seeking a Research Intern to work at the intersection of audio engineering and AI. You will help create an intelligent system that automatically optimizes audio performance in professional conference environments, analyzing mic settings, EQ, and noise suppression.

The role offers hands-on guidance in an international team, with a flexible work-from-home option one day per week and an internship allowance of €500–€600 per month.

Qualifications

• Affinity with digital signal processing (DSP) or audio processing fundamentals.
• Familiar with AI / Machine Learning concepts (e.g. supervised learning, optimization, adaptive systems).
• Experience in programming and algorithm development (e.g. Python, C/C++, or MATLAB).
• Enjoy system-level thinking, combining data, algorithms, sensors, and control logic.
• Interested in real-world engineering challenges, ideally within audio or embedded systems.
• Hands-on mindset and enjoy building and testing prototypes.
• Able to work independently, structure your work, and clearly communicate your results.

Responsabilités

• Understand the problem space by analyzing how professional audio configurations are currently used and identify key parameters such as microphone sensitivity, equalization, echo cancellation, and feedback suppression.
• Explore AI-driven solutions by researching and evaluating AI and signal-processing techniques for automatic audio optimization.
• Define data strategy by identifying relevant data sources and designing a robust data collection approach.
• Design intelligent systems by developing a concept for automated audio tuning, including model architecture, features, and learning approach (rule-based, ML, or hybrid).
• Build a Proof of Concept by implementing and prototyping your solution to demonstrate autonomous audio optimization.
• Test in real-world scenarios by evaluating performance in representative conference conditions (empty vs. occupied rooms).
• Assess impact & feasibility by analyzing robustness, practical integration, and added value within a professional audio ecosystem.

Connaissances

DSP / audio processing

AI / Machine Learning concepts

Python

MATLAB

C/C++

System-level thinking

Hands-on mindset

Independent work

Outils

Python

MATLAB

C/C++

Description du poste

Research Intern – AI-Based Audio Optimization (February 2027)

• Intern

At Keenfinity, we are a globally leading provider of innovative and professional security and communication solutions. With over 4,200 employees in over 50 countries worldwide, our ambition is clear: we offer more than just technology - we secure, connect, and amplify the moments that matter in life.

Next to our passion for technology we’re very passionate about our work environment. Based on values such as trust, appreciation, and accountability we all work together to shape the future - boldly, customer-focused and with a strong team spirit.

As a Research Intern, you’ll work on a cutting-edge challenge at the intersection of audio engineering and AI. Your goal is to help create an intelligent system that automatically optimizes audio performance in professional conference environments.

• Understand the problem space – Analyze how professional audio systems are currently configured and identify key parameters such as microphone sensitivity, equalization, echo cancellation, and feedback suppression
• Explore AI-driven solutions – Research and evaluate AI and signal-processing techniques for automatic audio optimization
• Define data strategy – Identify relevant data sources (e.g. audio signals, acoustic responses, system state, room occupancy) and design a robust data collection approach
• Design intelligent systems – Develop a concept for automated audio tuning, including model architecture, features, and learning approach (rule-based, ML, or hybrid)
• Build a Proof of Concept – Implement and prototype your solution to demonstrate autonomous audio optimization
• Test in real-world scenarios – Evaluate performance in representative conference conditions (empty vs. occupied rooms)
• Assess impact & feasibility – Analyze robustness, practical integration, and added value within a professional audio ecosystem

• You have an affinity with Digital Signal Processing (DSP) or audio processing fundamentals
• You are familiar with AI / Machine Learning concepts (e.g. supervised learning, optimization, adaptive systems)
• You have experience in programming and algorithm development (e.g. Python, C/C++, or MATLAB)
• You enjoy system-level thinking, combining data, algorithms, sensors, and control logic
• You’re interested in real-world engineering challenges, ideally within audio or embedded systems
• You have a hands-on mindset and enjoy building and testing prototypes
• You can work independently, structure your work, and clearly communicate your results

What We Offer:

• A hands-on internship in an international team.
• Close guidance from experienced professionals.
• A dynamic role where your input and ideas are appreciated.
• The option to work from home one day per week.
• An internship allowance between €500 and €600 per month (based on full-time employment).
• Phone meeting with a Keenfinity campus recruiter;
• Interview via Microsoft Teams with team members;
• Contract offers from Keenfinity.

At Keenfinity we don’t just build innovative solutions - we shape a smarter, more connected world through technology.

We value different backgrounds, ideas, and experiences and we’re committed to growing, learning, and celebrating success as one team. Everyone is welcome here - we foster an environment where everyone is respected, valued, and encouraged to be their authentic self.

Keenfinity is an equal opportunity employer, offering equal opportunities for all. We welcome applications from people with disabilities and can offer support, if needed. When everyone has a chance to contribute, we all do better.