ML Engineer – Speech & Voice (NXJ-212)

GPU-based microservices handle the core speech pipeline—STT consumption, word-level alignment, diarization, and speaker identification. The primary challenge isn't just serving models, but establishing rigorous data-driven evaluation to separate real accuracy gains from benchmark noise on difficult sports audio. The Senior ML Engineer will own the speech services, lead fair model bake-offs, and hold full authority over which models reach production.

The platform delivers real-time AI video processing and automated content generation for professional sports leagues globally. The underlying pipeline operates in high-noise live broadcast environments, demanding tight latency budgets, high throughput, and robust handling of overlapping speech and crowd noise.

Technology Stack: The platform delivers real-time AI video processing and automated content generation for professional sports leagues globally. The underlying pipeline operates in high-noise live broadcast environments, demanding tight latency budgets, high throughput, and robust handling of overlapping speech and crowd noise.

• Own and scale the core speech pipeline covering alignment, diarization, speaker identification, and enrollment signature-matching workflows.
• Optimize GPU inference performance for throughput, memory footprint, and cost through batching, precision tuning, and compilation.
• Build and maintain labeled sports test benchmarks stratified by speaker count, audio quality, language, and background noise.
• Define and track production evaluation metrics including DER, WER, word-level speaker attribution, speaker-count error, latency, and GPU cost.
• Conduct rigorous model bake-offs and write clear decision memos detailing trade-offs, licensing constraints, and statistical uncertainty.
• Maintain a shadow or A/B deployment framework to gate every production release with empirical evidence.

Why This Role Is Worth Your Time