Senior ML Engineer (Speech, Audio & NLP)

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SeniorZdalnie·GdańskFull-time·B2B

#472453·Dodano wczoraj·1

Źródło: justjoin.it

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Tech Stack / Keywords

PythonAIMachine LearningSpeech/Audio ProcessingNLP LLMASR

Podsumowanie oferty

You’ll develop, optimize, and improve end-to-end speech processing pipelines for an American mobile computing company. The work covers speech recognition, audio processing, and NLP, from raw audio input to structured text output.

Wymagania

Strong Python programming skills.
Strong problem-solving and analytical abilities.
Solid knowledge of machine learning and artificial intelligence.
Good understanding of speech processing, audio processing, and NLP concepts.
Hands-on experience with automatic speech recognition or speech-to-text systems.
Experience building or improving audio preprocessing and transcription pipelines.
Experience handling audio data, including formats, sampling rates, noise, segmentation, and audio quality issues.
Experience preparing and managing audio/text datasets for training, evaluation, and analysis.
Experience fine-tuning LLM and/or ASR models for task-specific or domain-specific use cases.
Experience evaluating ASR systems using metrics such as WER, CER, and task-specific quality metrics.
Experience performing ASR error analysis and identifying ways to improve transcription quality.
Experience with transcript post-processing, such as text normalization, punctuation restoration, casing, or domain-specific vocabulary correction.
Familiarity with deep learning frameworks such as PyTorch or similar.
Familiarity with speech/audio and ML tools such as Hugging Face Transformers/Datasets, torchaudio, librosa, pydub, soundfile, Pandas, and NumPy, or similar.
Experience with development and experiment tools such as Git/GitHub, Hydra, and Weights & Biases, or similar alternatives.
Experience working with shared codebases, remote teams, and remote servers.
Ability to independently own tasks, analyze performance, and proactively propose improvements.

Nice to have:

Experience with Whisper, wav2vec 2.0, NeMo, Kaldi, SpeechBrain, or similar speech frameworks/models.
Experience fine-tuning ASR models for specific domains, languages, accents, or noisy environments.
Experience with multilingual or low-resource ASR.
Experience with audio denoising or speech enhancement.
Experience with voice activity detection and advanced audio segmentation.
Experience with speaker diarisation, speaker verification, speaker identification, or speaker embedding models.
Experience with streaming or real-time ASR systems.
Experience with text-to-speech or voice synthesis.

Obowiązki

Develop, train, evaluate, and deploy machine learning models for speech and audio tasks.
Build and optimize end-to-end speech-to-text pipelines, including audio preprocessing, ASR, and transcript post-processing.
Prepare, clean, manage, and manipulate audio and text datasets for model development and evaluation.
Perform audio preprocessing, including resampling, normalization, denoising, segmentation, and format conversion.
Analyze ASR outputs and identify ways to improve transcription quality.
Improve ASR performance through data improvements, model tuning, pipeline optimization, and post-processing.
Apply NLP techniques for transcript cleanup, text normalization, punctuation restoration, casing, and domain-specific correction.
Evaluate speech and NLP systems using metrics such as WER, CER, precision, recall, and task-specific quality metrics.
Run and track experiments, document findings, and communicate model or pipeline improvements.
Collaborate with team members on shared codebases, remote projects, and remote servers.

Benefity

Bonuses for article writing, public talks, and other activities.
Time off including vacation, national holidays, sick leave, and family days.
Personalized learning programs tailored to your interests and skill development.
Free tech webinars and meetups organized by Svitla.
Regular corporate online activities.

Premie

Płatne święta

Spotkania integracyjne

Svitla Systems

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