{"id":14098,"url":"https://alion.io/job/bland-machine-learning-researcher-audio","title":"Machine Learning Researcher, Audio","company":{"id":15360,"name":"Bland","domain":"bland.ai","url":"https://alion.io/company/bland","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":74,"open_postings":16,"ghost_share":0.438,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":54,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":160000,"max":280000,"currency":"USD","period":"year","gross":null,"usd_annual":280000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ElevenLabs","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Quantization","optional":false},{"name":"Self-Supervised Learning","optional":false},{"name":"Speech Recognition","optional":false},{"name":"Text-to-Speech","optional":false},{"name":"Twilio","optional":false},{"name":"Voice Agents","optional":false}],"status":"live","first_seen_at":"2026-04-20T22:07:11Z","employer_posted_date":"2026-04-20","last_verified_at":"2026-10-17T12:00:40Z","board_verified":true,"closed_at":null,"days_open":179,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":179},"description":"Machine Learning Researcher, Audio\nLocation: San Francisco, CA or Remote\nAbout Bland\nAt Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco, we are a fast-growing team reimagining how customers interact with businesses through voice. We have raised $100 million from leading Silicon Valley investors, including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs.\nVoice is quickly becoming the primary interface between businesses and their customers. We are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human.\nThe Role: Machine Learning Researcher, Audio\nAs a Machine Learning Researcher at Bland, you'll be working on foundational research and development across the core components of our voice stack: speech-to-text, large language models, neural audio codecs, and text-to-speech. Your work will define how our agents understand, reason, and speak in real time at enterprise scale.\nThis is not a narrow research role. You will take ideas from theory to large-scale training to production inference systems serving millions of calls per day. You will design new modeling approaches, validate them with rigorous experimentation, and collaborate with engineering teams to deploy them into real customer environments.\nWhat You Will Do\nBuild and Scale Next-Generation TTS Systems\nDesign and train large scale text-to-speech models capable of expressive, controllable, human-sounding output.\n\nDevelop neural audio codec-based TTS architectures for efficient, high-fidelity generation.\n\nImprove prosody modeling, question inflection, emotional expression, and multi-speaker robustness.\n\nOptimize for real-time, low-latency inference in production.\n\nAdvance Speech-to-Text Modeling\nBuild and fine-tune large scale ASR systems robust to accents, noise, telephony artifacts, and code switching.\n\nLeverage self-supervised pretraining and large-scale weak supervision.\n\nImprove transcription accuracy for real-world enterprise scenarios, including structured extraction and conversational nuance.\n\nPioneer Neural Audio Codecs\nResearch and implement neural audio codecs that achieve extreme compression with minimal perceptual loss.\n\nExplore discrete and continuous latent representations for scalable speech modeling.\n\nDesign codec architectures that enable downstream generative modeling and controllable synthesis.\n\nDevelop Scalable Training Pipelines\nCurate and process massive audio datasets across languages, speakers, and environments.\n\nDesign staged training curricula and data filtering strategies.\n\nScale training across distributed GPU clusters focusing on cost, throughput, and reliability.\n\nRun Rigorous Experiments\nDesign ablation studies that isolate the impact of architectural changes.\n\nMeasure improvements using both objective metrics and perceptual evaluations.\n\nValidate ideas quickly through focused experiments that confirm or eliminate hypotheses.\n\nWhat Makes You a Great Fit\nDeep Research Foundations\nExperience with self-supervised learning, multimodal modeling, or generative modeling.\n\nAbility to derive new formulations and implement them efficiently.\n\nExpertise in Voice Modeling\nHands-on experience building or scaling TTS, STT, or neural audio codec systems.\n\nFamiliarity with large scale speech datasets and real-world audio variability.\n\nStrong intuition for audio quality, prosody, and conversational dynamics.\n\nSystems and Hardware Awareness\nExperience training and serving large models on modern accelerators.\n\nKnowledge of inference optimization techniques, including quantization, kernel optimization, and memory efficiency.\n\nUnderstanding of real-time constraints in telephony or streaming environments.\n\nExperimental Rigor\nTrack record of designing controlled experiments and meaningful ablations.\n\nComfortable working with both offline benchmarks and live production metrics.\n\nAbility to move quickly from hypothesis to validation.\n\nBuilder Mentality\nComfortable in fast-moving startup environments.\n\nStrong ownership mindset from research through deployment.\n\nExcited by ambiguous, unsolved problems.\n\nHow You Show Up\nYou treat unsolved problems as opportunities to invent new paradigms.\n\nYou identify the single experiment that can validate an idea in days, not months.\n\nYou measure everything and let data drive decisions.\n\nYou are obsessed with making voice agents sound truly human.\n\nYou use AI tools aggressively to amplify your own impact and accelerate research cycles.\n\nBonus Points\nExperience with large scale distributed training.\n\nResearch publications or open source contributions in speech or language AI.\n\nBackground in real-time speech systems or telephony.\n\nPhD in ML, AI, or a related field, or equivalent research impact.\n\nBenefits and Compensation\nHealthcare, dental, vision, all the good stuff\n\nMeaningful equity in a fast-growing company\n\nEvery tool you need to succeed\n\nBeautiful office in Levi's Plaza, SF with rooftop views\n\nCompetitive salary: $160,000 to $280,000\n\nIf you are energized by building and scaling TTS models, pioneering neural audio codecs, and pushing the boundaries of speech-to-text systems, we would love to hear from you.\nAdditional Information\nBland is an equal opportunity employer. We are committed to proving equal employment opportunities to all qualified applicants and employees and do not discriminate based on any legally protected characteristic. \nBland participates in the E-Verify employment verification program. All new hires are required to complete the Form I-9, and employment will be verified though E-Verify as part of the onboarding process.","description_format":"text","description_chars":5707,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Conversational AI","Speech & Audio AI","AI Agents"],"lifecycle":[{"event":"open","at":"2026-04-20T22:07:11Z"}],"visa":[],"liveness":{"score":8,"band":"cold","label":"Long shot","p_open":1,"p_active":0.3,"p_room":0.28,"age_days":179,"expected_fill_days":54,"reasons":["conf:0","ghost","win:tail","crowd:"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":280000,"is_top_pay":true},"html_url":"https://alion.io/job/bland-machine-learning-researcher-audio","json_url":"https://alion.io/job/bland-machine-learning-researcher-audio.json","meta":{"generated_at":"2026-10-17T13:24:10Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":17947,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-18T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":15360},"rest":"https://alion.io/mcp/rest/get_company?id=15360"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fbland-machine-learning-researcher-audio"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fbland-machine-learning-researcher-audio"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fbland-machine-learning-researcher-audio"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/bland-machine-learning-researcher-audio\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fbland-machine-learning-researcher-audio"}]}