ML Team Lead

Role overview Lead an applied machine learning team building speech systems for varied Southeast Asian languages, accents and real-world audio. The role combines hands-on technical leadership with team development: setting direction, maintaining production quality and helping the team turn experiments into measurable improvements.

Responsibilities - Set technical direction for speech and machine learning development across languages and audio conditions. - Lead, mentor and grow engineers and interns while encouraging clear ownership. - Guide work from experimentation through production integration and delivery. - Own production quality, including accuracy, robustness, latency and cost. - Establish evaluation standards, experiment practices and model quality benchmarks. - Identify recurring failures across languages and audio conditions, then drive solutions.

Requirements - At least four years in applied machine learning or speech engineering, including one to two years leading a team. - Strong Python and PyTorch skills and deep knowledge of speech recognition, speech processing and evaluation. - Experience deploying machine learning models in production systems. - Familiarity with GPU inference, optimization and production constraints. - Ability to set evaluation standards and communicate across research, engineering and business. - A hands-on leadership style, sound judgment with incomplete information and commitment to investigating failures.

Nice to have - Experience with multilingual or low-resource speech, especially Southeast Asian languages. - Exposure to on-device or low-latency inference. - Experience building evaluation pipelines or annotation workflows, or working on code-switching, accent robustness or noisy audio.

Benefits and work setup - Remote-first flexibility and the opportunity to shape a team and its technical direction. - Equity is offered; the role is equity-only, with no salary provided at this stage.