Senior Speech & NLP ML Engineer

Svitla Systems; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Remote work

Performance bonuses

Learning & development

Flexible schedule

Job summary

Svitla Systems is seeking a Senior Speech & NLP ML Engineer for a full-time role in Europe. You will design, train, and deploy end-to-end speech-to-text pipelines, optimizing ASR performance and transcript quality across multilingual contexts.

The ideal candidate combines software engineering with hands-on speech processing, NLP, and ML expertise, and thrives on solving complex technical challenges in a distributed, remote-friendly environment.

Qualifications

• Strong problem-solving and analytical abilities.
• Solid knowledge of machine learning and AI.
• Understanding of speech processing, audio processing and NLP.
• Hands-on ASR or STT experience.
• Experience building or improving audio preprocessing and transcription pipelines.
• Experience with audio data handling and quality issues.
• Experience preparing and managing audio/text datasets for training/evaluation.
• Fine-tuning LLM and/or ASR models for task/domain use cases.
• Experience evaluating ASR with WER/CER metrics.
• Experience ASR error analysis and transcription quality improvements.
• Transcript post-processing: normalization, punctuation, casing, domain terms.
• Familiarity with PyTorch and ML tooling like Hugging Face, torchaudio, librosa.
• Experience with Git/GitHub, Hydra, W&B, or similar.
• Experience working with remote teams and shared codebases.

Responsibilities

• Develop, train, evaluate, and deploy ML models for speech/audio tasks.
• Build end-to-end speech-to-text pipelines from preprocessing to post-processing.
• Prepare and curate audio/text datasets for model development and evaluation.
• Perform audio preprocessing: resampling, normalization, denoising, segmentation.
• Analyze ASR outputs and improve transcription quality.
• Improve ASR via data, model tuning, pipeline optimization, post-processing.
• Apply NLP techniques for transcript cleanup and domain-specific correction.
• Evaluate speech/NLP systems using WER, CER, precision, recall metrics.
• Run experiments, document findings, and share improvements with team.
• Collaborate on shared codebases and remote projects.

Skills

Problem solving

Machine learning

Speech processing

NLP concepts

ASR / STT

Audio preprocessing

Data handling

Dataset management

LLM fine-tuning

ASR evaluation (WER/CER)

Transcript post-processing

PyTorch

Hugging Face / Transformers

torchaudio / librosa

Git / GitHub

Hydra / Weights & Biases

Remote collaboration

Education

IT-related background

Tools

PyTorch

Hugging Face Transformers

torchaudio

librosa

pydub

soundfile

Pandas

NumPy

Git

Weights & Biases

Job description

Svitla Systems Inc. is looking for a Senior Speech & NLP ML Engineer for a full-time position (40 hours per week) in Europe. Our client is an American mobile computing company.

The ideal candidate combines strong software engineering expertise with hands‑on experience in speech recognition, audio processing, and NLP. We’re looking for someone who enjoys solving complex technical challenges, takes full ownership of their work, and continuously looks for ways to improve model performance and overall system efficiency.

You will work on developing, optimizing, and improving end-to-end speech processing pipelines, from raw audio input to accurate, structured text output.

Requirements:

• 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 with audio data handling, 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 tasks such as text normalisation, punctuation restoration, casing, or domain‑specific vocabulary correction.
• Familiarity with deep learning frameworks such as PyTorch or similar.
• Familiarity with speech/audio and ML tooling such as Hugging Face Transformers/Datasets, torchaudio, librosa, pydub, soundfile, Pandas, 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, analyse performance, and proactively propose improvements.

Nice to have:

• IT‑related background gained through formal education or hands‑on experience.
• Experience coordinating delivery activities or leading cross‑functional teams.
• Familiarity with financial regulations across European markets.

Will be a plus:

• 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 is a plus, but not required.

Responsibilities:

• Develop, train, evaluate, and deploy machine learning models for speech and audio‑related tasks.
• Build and optimise 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 tasks such as resampling, normalisation, denoising, segmentation, and format conversion.
• Analyse ASR outputs and identify ways to improve transcription quality.
• Improve ASR performance through data improvements, model tuning, pipeline optimisation, and post‑processing.
• Apply NLP techniques for transcript cleanup, text normalisation, 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 clearly.
• Collaborate with team members on shared codebases, remote projects, and remote servers.

We offer:

• US and EU projects based on advanced technologies.
• Competitive compensation based on skills and experience.
• Regular performance appraisals to support your growth.
• Flexibility in workspace, either remote or our welcoming office.
• Bonuses for article writing, public talks, and other activities.
• Generous time off, including vacation, national holidays, sick leaves, 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.

Awesome team and a friendly, supportive community!

Svitla Systems

Svitla Systems is a global digital solutions company with over 20 years of industry experience, presence across 15 countries, and a team of 1,000+ skilled tech experts, creators, and visionaries. We empower businesses ac... Company profile