ML Architect

Job Description

• Experience: We're looking for someone with over eight years of experience in Machine Learning, including at least three to five years in a lead or architect role focused on production systems. You should have deep expertise in designing and deploying end-to-end ML systems, especially for audio, signal processing, or time-series data.
• Technical Skills: You'll need strong proficiency with major ML frameworks like PyTorch or TensorFlow and related libraries such as NumPy and SciPy. Experience with various ML model architectures relevant to audio, like CNNs, RNNs, Transformers, GANs, and VAEs, is essential. A solid understanding of audio digital signal processing (DSP) fundamentals and experience with different audio data types are also required.
• MLOps and Programming: Familiarity with MLOps tools and practices such as MLflow or Kubeflow is necessary. Strong Python skills are a must, and experience with C++ is a significant advantage for integrating with our existing audio engines.
• Education and Leadership: A Bachelor's or Master's degree in a quantitative field like Computer Science, Electrical Engineering, or Machine Learning is required, while a Ph.D. is a plus. You should also have prior experience in a technical leadership role with a history of successful cross-functional collaboration.
• Communication: Exceptional communication, leadership, and interpersonal skills are crucial for articulating complex technical concepts to various audiences

Job Responsibilities

• Architect ML Systems: You will design and implement robust, scalable, and high-performance machine learning systems tailored for audio-centric applications. This includes creating generative models for musical ideas and developing intelligent audio processing solutions.
• Define ML Strategy: A key part of your role will be to translate the company's overall AI vision into concrete architectural blueprints and technical roadmaps. You'll ensure these plans align with product goals for initiatives focused on generative music tools and intelligent sound shaping.
• Evaluate and Select Technologies: You will lead the charge in assessing and choosing the most suitable ML technologies, frameworks, and tools. This will involve making sure they are compatible with our core DSP strengths and product environment.
• Shape Data Strategy: Collaboration is key! You'll work with data engineers and product teams to create strategies for acquiring, labeling, and managing the large audio datasets needed for training our models.
• Establish MLOps Practices: You will define and implement best practices for the entire machine learning model lifecycle, from training and versioning to deployment and monitoring.
• Optimize for Performance: A critical aspect of this role is designing ML solutions that are optimized for real-time performance, low latency, and efficiency, which is vital for audio applications.
• Provide Leadership and Mentorship: You'll guide and mentor ML engineers, fostering a culture of technical excellence and innovation within the team.
• Drive Integration and Research: You will work closely with DSP engineers, software developers, and product managers to seamlessly integrate ML capabilities into our products. Staying at the forefront of ML and audio AI research to identify new opportunities is also a key responsibility.

Department/Project Description

This is a senior technical leadership position within a company that has been a pillar of the professional audio industry for decades. We are known for our deep respect for classic recording technology combined with a relentless drive for innovation. Our unique strength lies in our ability to meticulously recreate the nuanced character of analog sound in the digital realm.

In this role, you will be pivotal in shaping the future of our products by architecting the machine learning systems that will power our next generation of creative tools. You will define the technical direction for key initiatives focused on using AI to enhance musical creativity and intelligently sculpt sound. Your work will involve designing scalable and high-performance ML architectures that integrate flawlessly with our existing digital signal processing and software ecosystem, directly impacting the creative experience of musicians and producers worldwide.