{"id":1267814,"url":"https://alion.io/job/umatr-aiml-engineer-voice-ai-speech-models","title":"AI/ML Engineer - Voice AI / Speech Models","company":{"id":2053453,"name":"UMATR","domain":"umatr.io","url":"https://alion.io/company/umatr","size_band":"11-50","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Riyadh, Saudi Arabia"],"countries":["SA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":49000,"max_usd":126000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2102},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch Lightning","optional":false},{"name":"Speech Recognition","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Transformers","optional":false},{"name":"Vertex AI","optional":false},{"name":"Voice Agents","optional":false}],"status":"closed","first_seen_at":"2026-05-19T11:27:04Z","employer_posted_date":"2026-09-28","last_verified_at":"2026-10-19T18:32:41Z","board_verified":false,"closed_at":"2026-10-19T18:32:41Z","days_open":153,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":152},"description":"Title: AI/ML Engineer - Voice AI / Speech Models / Real-Time Audio Systems\nTech Stack: Python, PyTorch, GCP, Vertex AI, Cloud Run, STT, TTS, Transformers, Audio ML, Real-Time Inference\nWhat You’ll Do:\nJoin a fast-scaling AI startup building a next-generation voice AI platform powering real-time enterprise communication systems across industries like banking, fintech, and customer operations.\nYou will work on the core AI layer behind real-time conversational systems, helping design, train, optimise, and deploy production-grade speech models used in live environments.\nThis is a highly applied AI role focused on taking models from research into production, with strong ownership across training, evaluation, inference, and deployment.\nKey responsibilities include:\nTraining and fine-tuning speech models across STT, TTS, and conversational voice AI use cases\nBuilding scalable ML pipelines for training, inference, and deployment\nImproving latency, speech quality, and real-time performance of voice systems\nWorking on modern deep learning architectures for speech and audio understanding\nDeploying production ML systems on GCP using services like Vertex AI and Cloud Run\nDesigning evaluation frameworks around accuracy, latency, robustness, and conversational quality\nCollaborating closely with engineering and product teams to ship real-world AI features into production systems\nWho They Are:\nA well-funded AI startup building advanced voice infrastructure and conversational AI products for enterprise customers across the Middle East.\nThe company operates at the intersection of speech AI, real-time systems, and enterprise automation, building technology across voice agents, speech infrastructure, workflow automation, and AI-powered communications.\nTheir products are already being deployed into enterprise environments, and the team is now scaling aggressively across AI research and engineering.\nThis is an opportunity to join an early but high-growth environment where engineers have direct ownership, fast feedback loops, and real impact on product direction.\nRequirements:\n5+ years of experience building ML or deep learning systems in production\nStrong Python engineering skills\nHands-on experience with PyTorch or PyTorch Lightning\nStrong understanding of deep learning fundamentals, transformers, optimisation, and sequence models\nExperience deploying ML systems end-to-end in cloud environments\nComfortable working in startup environments with fast iteration cycles\nSpeech AI / Voice AI experience (ASR, STT, TTS, conversational AI)\nExperience with real-time or low-latency inference systems\nExposure to distributed training or large-scale model optimisation\nUnderstanding of telephony, VoIP, or communications systems\nArabic or multilingual speech model experience","description_format":"text","description_chars":2786,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial 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