About this opportunity
Ova Technologies lists this Speech Recognition Engineer opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Job Title: Speech Recognition Engineer
Job Summary
We are seeking a Speech Recognition Engineer to design, develop, and optimize Automatic Speech Recognition (ASR) systems for voice-enabled applications. The ideal candidate will have expertise in speech processing, deep learning, natural language processing (NLP), and machine learning. This role involves building, training, fine-tuning, and deploying speech recognition models that deliver high accuracy, low latency, and robust performance across diverse languages, accents, and acoustic environments.
Key Responsibilities
Design, develop, and optimize Automatic Speech Recognition (ASR) models for production applications.
Build end-to-end speech processing pipelines, including audio preprocessing, feature extraction, decoding, and post-processing.
Train, fine-tune, and evaluate speech recognition models using large-scale speech datasets.
Improve recognition accuracy for multilingual, domain-specific, and noisy audio environments.
Develop real-time and batch speech recognition solutions.
Optimize models for latency, throughput, memory efficiency, and inference performance.
Integrate ASR models into voice assistants, conversational AI systems, call center platforms, and enterprise applications.
Develop data pipelines for speech data collection, annotation, augmentation, and quality validation.
Evaluate model performance using industry-standard speech recognition metrics.
Collaborate with NLP Engineers, Machine Learning Engineers, AI Engineers, Data Scientists, and Product teams.
Deploy speech recognition models using MLOps and cloud-native deployment practices.
Monitor production performance and continuously improve model quality.
Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Speech Technology, or a related field.
3+ years of experience in speech recognition, speech processing, machine learning, or AI engineering.
Strong programming skills in Python.
Experience with deep learning frameworks such as PyTorch or TensorFlow.
Solid understanding of digital signal processing (DSP) fundamentals.
Experience with speech processing libraries such as SpeechBrain, ESPnet, Hugging Face Transformers, torchaudio, librosa, or Kaldi.
Experience training and fine-tuning deep learning models.
Familiarity with Linux development environments, Git, and containerization using Docker.
Understanding of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
Preferred Qualifications Experience with modern ASR architectures such as Whisper, Conformer, wav2vec 2.0, DeepSpeech, or RNN-Transducer (RNN-T).
Experience deploying speech recognition models using ONNX Runtime, TensorRT, NVIDIA Triton Inference Server, or TorchServe.
Knowledge of multilingual and low-resource language speech recognition.
Experience with streaming speech recognition and real-time inference.
Familiarity with speech enhancement, voice activity detection (VAD), speaker diarization, and keyword spotting.
Experience with MLOps tools such as MLflow, Kubeflow, or cloud AI platforms.
Knowledge of Large Language Models (LLMs) for speech understanding and conversational AI.
Technical Skills Python
PyTorch
TensorFlow
Hugging Face Transformers
SpeechBrain
ESPnet
Kaldi
torchaudio
librosa
Whisper
wav2vec 2.0
Conformer
RNN-T
ONNX Runtime
TensorRT
NVIDIA Triton Inference Server
TorchServe
Docker
Git
Linux
AWS / Azure / Google Cloud Platform
Soft Skills Strong analytical and problem-solving skills
Excellent communication and collaboration
Attention to detail
Ability to work with cross-functional teams
Continuous learning mindset
Strong documentation and experimentation practices
Nice to Have Experience with speech synthesis (Text-to-Speech) or conversational AI platforms
Knowledge of multilingual ASR evaluation and benchmarking
Experience with edge AI deployment for speech applications
Familiarity with model compression, quantization, and inference optimization
Publications or contributions in speech AI, ASR, or related open-source projects
Key Performance Indicators (KPIs) Word Error Rate (WER) and Character Error Rate (CER)
Model inference latency and throughput
Speech recognition accuracy across languages and accents
Production model availability and reliability
Improvement in recognition quality over baseline models
Successful deployment and adoption of ASR features
Reduction in production defects and model regressions
Location
Hybrid / Remote / On-site (as applicable)
Employment Type
Full-time
Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.