Staff Machine Learning Engineer

Jeppesen ForeFlight builds industry-leading aviation software used by pilots, aircraft operators, and major airlines worldwide. They are seeking a Senior Machine Learning Engineer to help build and scale domain-specialized automatic speech recognition systems for aviation and operational audio workflows, focusing on developing optimized ASR models for high-accuracy transcription in safety-critical environments.

Responsibilities:

• Design, train, and optimize domain-specific ASR models for aviation and operational communications
• Develop verticalized speech models tuned for specialized terminology, accents, abbreviations, call signs, and noisy radio/audio conditions
• Build and maintain large-scale transcription and labeling pipelines for supervised and semi-supervised learning workflows
• Fine-tune foundation speech models (e.g., Whisper, wav2vec, Conformer, RNN-T, Citrinet, NeMo-based architectures) for aviation-specific use cases
• Improve transcription quality through language model adaptation, pronunciation lexicons, contextual biasing, and decoding optimization
• Develop evaluation frameworks and benchmarking methodologies using WER, CER, domain entity accuracy, latency, and robustness metrics
• Collaborate with product, avionics, data engineering, and platform teams to deploy scalable real-time and batch transcription systems
• Optimize inference pipelines for edge, cloud, and low-latency streaming environments
• Research emerging techniques in speech enhancement, diarization, speaker adaptation, multilingual ASR, and audio foundation models
• Ensure compliance with security, privacy, and operational reliability standards required in aviation environments

Requirements:

• Bachelor's or Master's degree in Computer Science, Machine Learning, Electrical Engineering, Linguistics, or related field
• 3+ years of experience in speech recognition, audio ML, or applied machine learning
• Strong experience training and fine-tuning ASR models using frameworks such as PyTorch or TensorFlow
• Experience with modern ASR architectures including: Transformer-based ASR, Conformer, RNN-T, CTC-based systems, Encoder-decoder speech models
• Experience working with: Speech/audio preprocessing, Forced alignment, Language model adaptation, Beam search decoding, Noise robustness techniques
• Familiarity with NVIDIA NeMo, Kaldi, ESPnet, Hugging Face, Whisper, DeepSpeed, or equivalent ecosystems
• Strong Python engineering skills and experience building production ML systems
• Experience with cloud infrastructure and ML deployment workflows (AWS, Kubernetes, Docker, CI/CD)
• Ability to work with large audio datasets and distributed training environments
• Experience building ASR systems for aviation, air traffic control, public safety, defense, or other mission-critical domains
• Familiarity with VHF/UHF radio communications and noisy-channel audio processing
• Experience with multilingual or code-switching ASR systems
• Background in speech enhancement, keyword spotting, diarization, or speaker verification
• Knowledge of LLM-assisted transcription correction and retrieval-augmented speech systems
• Experience optimizing models for real-time streaming inference
• Active pilot experience or familiarity with aviation operations is a plus