{"schemaVersion":"jobsearcher.job.v1","id":"534e1ab133b0885f5ab123b3","url":"https://jobsearcher.com/jobs/534e1ab133b0885f5ab123b3","canonicalUrl":"https://jobsearcher.com/jobs/534e1ab133b0885f5ab123b3","title":"Machine Learning Engineer","description":"About Bland\nAt Bland.com, our goal is to empower enterprises to make AI-phone agents at scale. Based out of San Francisco, we're a quickly growing team striving to change the way customers interact with businesses. We've raised $65 million from Silicon Valley's finest; Including Emergence Capital, Scale Venture Partners, YC, the founders of Twilio, Affirm, ElevenLabs, and many more.\nAbout the Role\nAs a Senior ML Engineer at Bland, you'll own the intelligence behind our voice AI platform. You're not just optimizing models—you're architecting the ML systems that make our agents sound genuinely human and drive real business outcomes for enterprise customers. Your work directly impacts whether our agents can handle complex, nuanced conversations or sound like corporate robots.\nWhat You'll Do\nOwn the full ML stack: Lead engineering and optimization efforts for our self-hosted STT, LLM, and TTS systems from research through production deployment.\nBuild production-grade inference systems: Design and implement high-throughput ML infrastructure serving millions of daily voice interactions with sub-second latency requirements.\nDrive model performance: Research and implement novel approaches to improve our models' conversational quality, RAG pipelines, and reduce latency,\nOptimize for enterprise scale: Handle complex inference optimization challenges—model quantization, efficient serving architectures, and cost optimization for large-scale deployments.\nCollaborate across teams: Work closely with Deployment Engineers to understand customer requirements and translate business needs into ML solutions that actually work in production.\nPush the boundaries: Experiment with cutting-edge techniques in conversational AI, real-time speech processing, and multi-modal understanding to keep Bland at the forefront of voice AI.\nWhat Makes You a Great Fit\nDeep ML expertise: 3+ years in machine learning with 1+ years focused on speech, or conversational AI. You've shipped ML systems that real users depend on.\nExperience with TTS/STT systems: You get your hands dirty with any new emerging technologies in this space, and are implementing novel solutions.\nSpecialist: You don’t have to have experience with the entire STT, LLM, TTS stack. We want someone who can narrow down on a specific problem and understand it in and out.\nProduction experience: You've built and scaled ML infrastructure from 0-1 and 1-100. You know the difference between a research prototype and a system that works at enterprise scale.\nFull-stack mindset: Comfortable working across the entire ML pipeline—data, training, inference, monitoring, and everything in between.\nStartup DNA: You've thrived in fast-moving environments where you own outcomes, not just tasks. You're comfortable with ambiguity and excited by the challenge of figuring things out.\nBonus Points If You Have\nExperience with real-time speech processing, TTS/ STT, or telephony systems\nBackground in large-scale distributed training and inference\nExperience with conversational AI, chatbots, or voice assistants\nPhD in ML/AI or equivalent research experience\nHow You Show Up\nOwnership mindset: You take full responsibility for your systems' performance and never wait for someone else to solve problems you can tackle.\nQuality obsessed: You care deeply about the craft—our agents should sound truly human, not like phone trees.\nData-driven: You measure everything, run rigorous experiments, and let results guide decisions.\nCollaborative: You work seamlessly with engineers, deployment teams, and customers to deliver solutions that actually work.\nRelentless: You push through ambiguous challenges and complex technical problems until you find solutions.\nBenefits and Pay:\nHealthcare, dental, vision, all the good stuff\nMeaningful equity in a fast-growing company\nEvery tool you need to succeed\nBeautiful office in Jackson Square, SF with rooftop views\nIf you don't have the perfect experience that is fine! We're a bunch of drop-outs and hackers. Working at a start-up is really hard. We work a lot and we figure things out on the fly. Please note, however, for this position machine learning experience at an United States based company is required.\nCompensation Range: $140,000-$250,000\nCompensation Range: $140K - $250K","company":"Bland","rawCompany":"bland","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-04-12T21:26:13.004Z","occupations":[{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"About Bland\nAt Bland.com, our goal is to empower enterprises to make AI-phone agents at scale. Based out of San Francisco, we're a quickly growing team striving to change the way customers interact with businesses. We've raised $65 million from Silicon Valley's finest; Including Emergence Capital, Scale Venture Partners, YC, the founders of Twilio, Affirm, ElevenLabs, and many more.\nAbout the Role\nAs a Senior ML Engineer at Bland, you'll own the intelligence behind our voice AI platform. You're not just optimizing models—you're architecting the ML systems that make our agents sound genuinely human and drive real business outcomes for enterprise customers. Your work directly impacts whether our agents can handle complex, nuanced conversations or sound like corporate robots.\nWhat You'll Do\nOwn the full ML stack: Lead engineering and optimization efforts for our self-hosted STT, LLM, and TTS systems from research through production deployment.\nBuild production-grade inference systems: Design and implement high-throughput ML infrastructure serving millions of daily voice interactions with sub-second latency requirements.\nDrive model performance: Research and implement novel approaches to improve our models' conversational quality, RAG pipelines, and reduce latency,\nOptimize for enterprise scale: Handle complex inference optimization challenges—model quantization, efficient serving architectures, and cost optimization for large-scale deployments.\nCollaborate across teams: Work closely with Deployment Engineers to understand customer requirements and translate business needs into ML solutions that actually work in production.\nPush the boundaries: Experiment with cutting-edge techniques in conversational AI, real-time speech processing, and multi-modal understanding to keep Bland at the forefront of voice AI.\nWhat Makes You a Great Fit\nDeep ML expertise: 3+ years in machine learning with 1+ years focused on speech, or conversational AI. You've shipped ML systems that real users depend on.\nExperience with TTS/STT systems: You get your hands dirty with any new emerging technologies in this space, and are implementing novel solutions.\nSpecialist: You don’t have to have experience with the entire STT, LLM, TTS stack. We want someone who can narrow down on a specific problem and understand it in and out.\nProduction experience: You've built and scaled ML infrastructure from 0-1 and 1-100. You know the difference between a research prototype and a system that works at enterprise scale.\nFull-stack mindset: Comfortable working across the entire ML pipeline—data, training, inference, monitoring, and everything in between.\nStartup DNA: You've thrived in fast-moving environments where you own outcomes, not just tasks. You're comfortable with ambiguity and excited by the challenge of figuring things out.\nBonus Points If You Have\nExperience with real-time speech processing, TTS/ STT, or telephony systems\nBackground in large-scale distributed training and inference\nExperience with conversational AI, chatbots, or voice assistants\nPhD in ML/AI or equivalent research experience\nHow You Show Up\nOwnership mindset: You take full responsibility for your systems' performance and never wait for someone else to solve problems you can tackle.\nQuality obsessed: You care deeply about the craft—our agents should sound truly human, not like phone trees.\nData-driven: You measure everything, run rigorous experiments, and let results guide decisions.\nCollaborative: You work seamlessly with engineers, deployment teams, and customers to deliver solutions that actually work.\nRelentless: You push through ambiguous challenges and complex technical problems until you find solutions.\nBenefits and Pay:\nHealthcare, dental, vision, all the good stuff\nMeaningful equity in a fast-growing company\nEvery tool you need to succeed\nBeautiful office in Jackson Square, SF with rooftop views\nIf you don't have the perfect experience that is fine! We're a bunch of drop-outs and hackers. Working at a start-up is really hard. We work a lot and we figure things out on the fly. Please note, however, for this position machine learning experience at an United States based company is required.\nCompensation Range: $140,000-$250,000\nCompensation Range: $140K - $250K","datePosted":"2026-04-12T21:26:13.004Z","dateModified":"2026-04-12T21:26:13.004Z","hiringOrganization":{"@type":"Organization","name":"Bland","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"534e1ab133b0885f5ab123b3"},"url":"https://jobsearcher.com/jobs/534e1ab133b0885f5ab123b3"}}