Software Engineer

Company Description

JoyMetric is a music technology startup focused on developing AI-powered tools that transform how musicians, DJs, and producers interact with audio. Our mission is to make advanced audio processing and music manipulation accessible through intuitive, real-time applications. We combine machine learning, digital signal processing, and GPU-accelerated computing to build innovative solutions for creative audio workflows. JoyMetric promotes a collaborative, remote-friendly environment where engineers have the opportunity to experiment with cutting-edge technologies, contribute to technical decisions, and play a meaningful role in shaping the future of AI-driven music production.

Role Description

This is a remote Software Engineer role at JoyMetric. The engineer will contribute to the design, development, and optimization of AI-powered audio processing systems, with a particular focus on real-time performance, GPU acceleration, and machine learning integration.

Day-to-day responsibilities include developing and optimizing audio processing pipelines, implementing GPU-accelerated algorithms using CUDA, integrating machine learning models into production applications, and improving system performance and latency. The engineer will also collaborate on building reliable software infrastructure, debugging complex technical challenges, and developing new capabilities for real-time audio manipulation.

The role offers an opportunity to work at the intersection of artificial intelligence, audio engineering, and high-performance computing while contributing directly to an innovative music technology product.

Qualifications

• Strong Software Engineering and Software Development skills, including experience designing, implementing, and maintaining reliable software systems.
• Knowledge of CUDA programming and GPU computing, including an understanding of parallel processing, GPU memory management, and performance optimization.
• Personal experience working with Digital Audio Workstations (DAWs) such as Ableton Live, FL Studio, Logic Pro, or similar music production software.
• Proficiency in Python and familiarity with C++ or other performance-oriented programming languages.
• Experience with machine learning frameworks such as PyTorch and an understanding of neural network inference and optimization.
• Understanding of digital audio processing concepts, including audio signals, sampling rates, latency, buffering, and real-time processing.
• Familiarity with GPU-accelerated machine learning workflows and deploying models into practical applications.
• Experience with Git, debugging, performance profiling, and modern software development practices.
• Strong analytical thinking, problem-solving abilities, and the ability to work independently in a remote environment.
• Interest in music production, audio technology, and AI-driven creative tools.
• Bachelor's degree in Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, or equivalent practical experience.

Nice to Have

• Experience with digital signal processing (DSP) and real-time audio systems.
• Familiarity with audio machine learning models, neural audio codecs, or generative audio technologies.
• Experience optimizing inference pipelines for low-latency applications.
• Experience developing audio plugins (VST/AU) or integrating software with existing music production workflows.
• Previous experience working in a startup or developing experimental AI products.

Compensation & Equity

This is an equity-only opportunity with no fixed salary or cash compensation at this stage. We are looking for an entrepreneurial Software Engineer who is excited about music technology and wants to become part of JoyMetric's founding team.

The position offers flexible working hours and the opportunity to contribute alongside other professional commitments. Equity ownership, vesting terms, and responsibilities will be discussed individually and formalized in a written agreement.

This opportunity is best suited for someone interested in long-term ownership, technical innovation, and helping build an early-stage startup.