Staff Machine Learning Engineer

Jeppesen ForeFlight builds industry-leading aviation software used by pilots, aircraft operators, and major airlines worldwide. As a high-growth, private equity-backed company, we are focused on scaling our operations, strengthening our financial infrastructure, and driving operational excellence across the business. Our team combines deep domain expertise with a collaborative, high-performance culture to solve complex challenges and support continued growth. Jeppesen ForeFlight is seeking a Senior Machine Learning Engineer to help build and scale domain-specialized automatic speech recognition (ASR) systems for aviation and operational audio workflows. This role focuses on developing vertical ASR models optimized for high-accuracy transcription in noisy, safety-critical environments, including aviation communications, cockpit interactions, operational dispatch, maintenance coordination, and related specialized audio domains. You will work across the full ML lifecycle — data engineering, model training, evaluation, deployment, and optimization — to deliver production-grade speech intelligence capabilities integrated into ForeFlight and broader aviation platforms. This position is ideal for someone with deep expertise in speech AI, acoustic modeling, large-scale transcription pipelines, and domain adaptation techniques for specialized vocabularies and constrained communication environments. **Key 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. **Required Qualifications** - 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. **Preferred Qualifications** - 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 multilingu…