Position: Audio Machine Learning Engineer
Company: Svitla Systems
Experience required: 3y
Category: Data Science
English level: upper
Published: 2022-05-01T00:00:00+03:00

**Requirements:**
- Expert at real-time, embedded ARM processing for real-time audio streaming. This includes experience with optimization techniques to reduce CPU and memory requirements (arm64, arm32, neon intrinsics).
- Experience with build tools (CMake).
- Experience in using Source Control / Project Tracking systems (Github, Jira).
- Experience using various techniques for robust data acquisition.
- BS in Acoustical, Audio, Electrical, or Computer Engineering.

In addition, preferable skills and behaviors include:
- Passionate about your work, bringing a motivated, positive attitude.
- Be a team player, basing decisions on what’s best for the team’s performance.
- Desire to work to high standards of code readability/documentation, while working to strict regular deadlines.
- Desire to create robust, maintainable code, automating repeated tasks to keep the team efficient and your daily work interesting.
- Strong ability to work collaboratively with other disciplines such as Acoustical,
- Mechanical, Electrical Engineering as well as machine learning and firmware developers.

**Will be a plus:**
- Knowledge of real-time digital audio communication algorithms and approaches, and ability to understand core audio concepts.
- Experience in developing and deploying real-time algorithms using fundamental digital signal processing methods/techniques.
- Knowledge of digital filter (IIR and FIR) theory and practice.

**Responsibilities:**
- Be the interface between the Audio Machine Learning team and real-time audio pipeline.
- Determine API requirements for an interface with the real-time audio pipeline.
- Assist the Audio Machine Learning team to integrate, and testing new machine learning iterations.
- Strive to the highest coding standards.
- Be passionate about CI/CD, and automation.
- Be capable of understanding audio terminology, and be a fast learner.
- Write clean, readable code.
- Share your understanding with teammates via documentation.
- Be comfortable presenting your work to the wider team.