Machine Learning Operations (MLOps) Engineer – LLM, Internal Systems $$$

Domain: Audio/Sound recording
Job Description

Qualifications:

• 3+ years of experience in Machine Learning Engineering, Applied AI, or related roles, with experience building and shipping production applications.
• Hands-on experience developing applications with LLMs (e.g., OpenAI APIs, open-source models, LangChain, LlamaIndex, or similar).
• Strong proficiency in Python and experience building scalable, user-facing systems or APIs.
• Experience designing and deploying interactive or real-time AI systems.
• Solid understanding of LLM concepts, including prompt engineering, retrieval-augmented generation (RAG), and model evaluation.
• Familiarity with cloud-based ML infrastructure (AWS, SageMaker, or similar), with the ability to collaborate effectively with MLOps teams.
• Clear grasp of latency, cost, and performance trade-offs when serving LLMs in production.
• Bonus: Familiarity with music production workflows, DAWs, or audio plugins.

Education:

• Bachelor’s or Master’s degree in Computer Science, related technical field, or equivalent practical experience.

Job Responsibilities

You will develop customer-facing AI experiences and contribute to the systems that support them. This includes:

• LLM Application Development: Design and build interactive, user-facing LLM-powered features such as virtual assistants, creative copilots, and intelligent workflow tools integrated into our products.
• Product Integration: Work closely with product, design, and audio engineering teams to embed AI capabilities directly into DAWs, plugins, and user-facing platforms.
• LLM Deployment & Optimization: Implement efficient, low-latency model serving strategies for real-time user interactions, balancing performance, cost, and responsiveness.
• Prompt & Interaction Design: Develop robust prompt engineering and response strategies tailored to creative workflows, ensuring high-quality, context-aware user experiences.
• Collaboration with ML Platform Teams: Partner with cloud and infrastructure engineers to leverage and extend existing pipelines (e.g., AWS SageMaker) for production deployment.
• User-Centric Iteration: Analyze usage patterns and feedback to continuously improve AI-driven features and ensure they provide clear value to musicians and creators.

Department/Project Description

The company is looking for a Machine Learning Engineer to help build and deliver next-generation AI-powered experiences for our customers. This role focuses on developing outward-facing LLM applications, such as intelligent assistants, creative tools, and interactive features integrated into our digital audio workstation and plugin ecosystem.

While you will work with state-of-the-art Large Language Models and collaborate with infrastructure teams, the core of this role is application development: designing, building, and deploying engaging, real-time AI features that enhance music creation workflows and delight our users.