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ML Engineer -Signal Processing / ASR

2 weeks, 6 days ago
India
Full-time
Senior
Machine Learning Engineer
Software Development
Docker FastAPI Kubernetes LLM Machine Learning Python PyTorch TensorFlow
Apply Now
Fresh Prints

Fresh Prints

Fresh Prints specializes in providing custom apparel and promotional products, offering over 1000 designs and 500 branded items tailored to the latest retail fashion trends, with a focus on serving student groups and organizations across various campuses.

Textiles, Apparel & Luxury Goods
251-1K
Founded 2009
View All Jobs 28

Description

  • Design, build, and improve ASR, audio, and speech-related ML systems for production.
  • Develop signal processing pipelines for noisy, compressed, telephony-style, and other real-world audio.
  • Train, fine-tune, evaluate, and deploy models for ASR, audio classification, diarization, redaction, and related tasks.
  • Own ML workflows end-to-end, including data preparation, training, validation, inference, monitoring, and iteration.
  • Optimize inference for latency, throughput, cost, and reliability.
  • Debug model quality issues using data analysis, targeted evaluations, and production monitoring.
  • Collaborate with product and engineering teams to translate business problems into practical ML solutions.
  • Investigate and resolve production issues such as ASR quality drops, latency spikes, and redaction edge cases.

Requirements

  • At least 5 years of hands-on experience deploying ASR or other ML systems in production.
  • Strong background in signal processing, speech recognition, audio ML, or telephony/audio pipelines.
  • Experience with production ASR systems, streaming inference, VAD, noise handling, diarization, speaker/channel issues, or similar speech technologies.
  • Strong Python engineering skills and experience building production services.
  • Experience with frameworks such as PyTorch, TensorFlow, JAX, ONNX Runtime, or similar.
  • Experience deploying models with Docker, Kubernetes, FastAPI, Triton, vLLM, TorchServe, custom inference services, or cloud ML platforms.
  • Strong understanding of model evaluation, regression testing, observability, latency, memory, GPU/CPU utilization, and cost-performance tradeoffs.
  • Comfort working with messy real-world data, noisy labels, domain drift, and ambiguous production issues.
  • Experience with real-time ASR, call-center audio, VoIP, or telephony systems is preferred.
  • Experience with Whisper, NVIDIA NeMo, Kaldi, wav2vec, HuBERT, Conformer, RNN-T, CTC, or transformer-based ASR is preferred.
  • Experience with PCI/PII redaction, compliance-sensitive ML systems, or privacy-preserving workflows is preferred.
  • Experience optimizing inference with ONNX, TensorRT, quantization, distillation, batching, or GPU serving is preferred.
  • Experience with LLMs, RAG, embeddings, rerankers, or prompt-based systems layered on ASR transcripts is preferred.

Interested in this position?

Apply directly on the company website

Apply Now

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