What You'll Be Doing

• Building and productising machine learning models for speech-to-text, text-to-speech, and speech-to-speech tasks

• Translating academic and internal research into scalable, maintainable code and services

• Developing and maintaining training pipelines, inference services, and deployment workflows

• Implementing robust data pipelines for sourcing, preprocessing, and versioning multimodal datasets

• Collaborating with research scientists to refine model architectures and integrate the latest techniques into production

• Evaluating model performance with custom metrics and developing automated test frameworks for ML systems

• Contributing to MLOps tooling and infrastructure to support model lifecycle management and monitoring in production

• Working closely with product, research, and backend engineering to deliver seamless end-to-end features

What We're Looking For

• Strong engineering background with experience shipping ML systems to production

• Deep familiarity with speech technologies (ASR, TTS), LLMs, or multimodal machine learning

• Proficient in Python, with expertise in ML frameworks such as PyTorch

• Experience building scalable ML pipelines (training, validation, deployment, monitoring)

• Knowledge of Docker, Kubernetes, and ML deployment platforms

• Comfort reading and adapting recent research papers into performant implementations

• Strong debugging and optimisation skills, particularly around model inference speed

• Experience working in cross-functional teams and contributing to engineering culture and best practices

• Bonus: experience with streaming audio processing, real-time systems, or speech synthesis engines

Why Join Us?

• Be part of a foundational team building novel, multimodal AI capabilities

• Shape the architecture and product direction from an early stage

• Work in a fast-moving, collaborative environment with a strong focus on execution and innovation

• Opportunity to grow alongside a rapidly scaling AI startup