Senior Backend Engineer - Speech Platform

• Build the audio data pipeline: mine our call archive, transcode, resample, segment, deduplicate and quality-filter at scale
  
• Build and operate real-time inference services with hard latency targets, including streaming, cancellation and mid-utterance interruption
  
• Integrate speech services into our existing Java-based platform and telephony infrastructure
  
• Instrument the full latency budget end to end and find where the milliseconds go
  
• Stand up training infrastructure — GPU scheduling, checkpointing, experiment tracking, reproducibility
  
• Own compute cost and concurrency economics: how many simultaneous calls per GPU, and how to improve it
  
• Support on-premise deployment for clients who can't send data outside their network
  

Requirements

• 3–4 years building and operating production backend systems
  
• Strong Java — you've owned services in production, not just contributed to them
  
• Working Python — enough to build data pipelines and integrate with ML tooling
  
• Real-time or low-latency systems experience: streaming APIs, WebSocket or gRPC streaming, concurrency, backpressure
  
• Data pipelines at scale (Airflow, Dagster, Spark or equivalent)
  
• Docker and Kubernetes in production
  
• Cloud infrastructure (AWS/GCP/Azure)
  
• Comfortable debugging performance: profiling, latency percentiles, throughput under load
  

• Serving ML models in production (Triton, vLLM, TorchServe)
  
• Audio tooling — ffmpeg, sox, codecs, resampling
  
• Telephony — SIP, Asterisk/FreeSWITCH, media servers, narrowband codecs
  
• MLOps tooling: MLflow, Weights & Biases, DVC
  
• GPU-aware infrastructure work