{"id":2428657,"url":"https://alion.io/job/svitla-systems-senior-speech-nlp-ml-engineer-2","title":"Senior ML Engineer (Speech, Audio & NLP)","company":{"id":2216,"name":"Svitla Systems","domain":"svitla.com","url":"https://alion.io/company/svitla-systems","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":79,"open_postings":7,"ghost_share":0,"stale_share":0.857,"repost_share":0,"time_to_fill_p50_days":44,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CZ","DK","FI","HU","IE","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":31,"salary":null,"salary_estimate":{"min_usd":109000,"max_usd":245000,"period":"year","method":"global_role_seniority_cell","sample_n":2216},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kaldi","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NumPy","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"Pandas","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Speech Recognition","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Transformers","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Whisper","optional":false}],"status":"live","first_seen_at":"2026-10-13T08:09:33Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-20T08:30:22Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"Svitla Systems Inc. is looking for a Senior Speech & NLP ML Engineer or a full-time position (40 hours per week) in Europe. Our client is an American mobile computing company.\nThe 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.\nYou will work on developing, optimizing, and improving end-to-end speech processing pipelines, from raw audio input to accurate, structured text output.\nRequirements\nStrong Python programming skills.\nStrong problem-solving and analytical abilities.\nSolid knowledge of machine learning and artificial intelligence.\nGood understanding of speech processing, audio processing, and NLP concepts.\nHands-on experience with automatic speech recognition or speech-to-text systems.\nExperience building or improving audio preprocessing and transcription pipelines.\nExperience with audio data handling, including formats, sampling rates, noise, segmentation, and audio quality issues.\nExperience preparing and managing audio/text datasets for training, evaluation, and analysis.\nExperience fine-tuning LLM and/or ASR models for task-specific or domain-specific use cases.\nExperience evaluating ASR systems using metrics such as WER, CER, and task-specific quality metrics.\nExperience performing ASR error analysis and identifying ways to improve transcription quality.\nExperience with transcript post-processing tasks such as text normalisation, punctuation restoration, casing, or domain-specific vocabulary correction.\nFamiliarity with deep learning frameworks such as PyTorch or similar.\nFamiliarity with speech/audio and ML tooling such as Hugging Face Transformers/Datasets, torchaudio, librosa, pydub, soundfile, Pandas, NumPy, or similar.\nExperience with development and experiment tools such as Git/GitHub, Hydra, and Weights & Biases, or similar alternatives.\nExperience working with shared codebases, remote teams, and remote servers.\nAbility to independently own tasks, analyse performance, and proactively propose improvements.\nWill be a plus\nExperience with Whisper, wav2vec 2.0, NeMo, Kaldi, SpeechBrain, or similar speech frameworks/models.\nExperience fine-tuning ASR models for specific domains, languages, accents, or noisy environments.\nExperience with multilingual or low-resource ASR.\nExperience with audio denoising or speech enhancement.\nExperience with voice activity detection and advanced audio segmentation.\nExperience with speaker diarisation, speaker verification, speaker identification, or speaker embedding models.\nExperience with streaming or real-time ASR systems.\nExperience with text-to-speech or voice synthesis is a plus, but not required.\nResponsibilities\nDevelop, train, evaluate, and deploy machine learning models for speech and audio-related tasks.\nBuild and optimise end-to-end speech-to-text pipelines, including audio preprocessing, ASR, and transcript post-processing.\nPrepare, clean, manage, and manipulate audio and text datasets for model development and evaluation.\nPerform audio preprocessing tasks such as resampling, normalisation, denoising, segmentation, and format conversion.\nAnalyse ASR outputs and identify ways to improve transcription quality.\nImprove ASR performance through data improvements, model tuning, pipeline optimisation, and post-processing.\nApply NLP techniques for transcript cleanup, text normalisation, punctuation restoration, casing, and domain-specific correction.\nEvaluate speech and NLP systems using metrics such as WER, CER, precision, recall, and task-specific quality metrics.\nRun and track experiments, document findings, and communicate model or pipeline improvements clearly.\nCollaborate with team members on shared codebases, remote projects, and remote servers.","description_format":"text","description_chars":3960,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"United Kingdom","iso":"GB","kind":"region"},{"name":"Austria","iso":"AT","kind":"region"},{"name":"Belgium","iso":"BE","kind":"region"},{"name":"Bulgaria","iso":"BG","kind":"region"},{"name":"Croatia","iso":"HR","kind":"region"},{"name":"Czech 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& Platform Engineering","IT Outsourcing & Dedicated Teams","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-13T08:19:15Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"Filed H-1B visas in the last two years","filings_12m":0,"filings_prev_12m":1,"green_card_filings_12m":0,"median_offered_wage_usd":null,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":90,"band":"hot","label":"Hiring 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