Machine Learning Engineer

Join our R&D team as an ML specialist to research, develop and ship technologies that change how people create sound. We're building systems that understand, manipulate and generate audio in ways that feel genuinely intuitive to professionals and we're nowhere near done. You'll own problems end-to-end, from identifying the right approach to getting it in front of customers, working closely with product to make sure what we build actually matters.

Key objectives

• Research and develop multimodal AI technologies that improve the way people work with sound
• Build and optimise LLM-powered audio pipelines and extend our Qwen-based vision model for audio production use cases
• Identify opportunities to apply the latest advances in generative AI and multimodal research to the professional audio field

Responsibilities

• Work within the team and research engineers to solve problems for film makers & sound designers
• Design and maintain backend inference systems that meet the latency and quality demands of professional audio workflows
• Collaborate with product and engineering teams to implement ML research in commercial products
• Work with the product owner to identify where ML creates the most value for customers
• Clearly and effectively communicate ML concepts, model behaviour and tradeoffs to the wider business
• Provide technical guidance on model architecture, fine-tuning strategy and deployment decisions

Essential:

• A degree in a relevant field or extensive professional experience
• Experience in commercial machine learning research and development
• Strong hands-on experience fine-tuning and adapting large language models (LoRA, QLoRA, PEFT, DPO/RLHF)
• Experience working with data, training and evaluating machine learning models
• Experience with multimodal architectures - audio-language, vision-language, or both
• Extensive audio and signal processing knowledge - spectral features, neural codecs, generative audio models
• Experience deploying models to cloud inference (AWS or GCP) with awareness of latency and cost tradeoffs
• MLOps competency - experiment tracking, model versioning, evaluation pipelines, ML CI
• Experience with Python and modern ML frameworks (PyTorch, JAX)
• Excellent verbal and written English communication skills
• Excellent analytical and problem-solving skills
• A desire to innovate and push current practice

Desirable:

• Experience with vision-language models, particularly Qwen-VL or similar
• Experience with Agile software development practices
• Familiarity with VST/AU plugin architectures and real-time audio constraints
• Experience delivering ML technologies shipped in commercial audio software
• Knowledge of sound design and audio post-production workflows
• C++ reading ability
• Previously registered audio machine learning patents

• Competitive salary and benefits package
• Private health insurance
• Opportunities for professional growth and development
• Flexible, remote working environment
• Access to cutting-edge technology and tools
• Exciting projects in a fast-growing, innovative company