The OpportunityCephable is building the future of privacy-first, on-device AI that helps people control, create, and automate across software on-device agents, speech, computer use, and more. Our technology runs locallyoffline, secure, and fastacross consumer and enterprise environments, including productivity software and games.We work at the intersection of speech recognition, multimodal ML, generative and reasoning models, and real-time systems, optimized for modern CPUs, GPUs, and NPUs.Role Overview We are seeking a Lead Machine Learning Engineer to own and advance Cephables core ML systems. This role is highly hands-on and technical, with responsibilities spanning model development, fine-tuning, optimization, quantization, testing, and deployment across on-device environments.You will lead the design and implementation of ML models for speech recognition, natural language understanding, generative and reasoning tasks, and multimodal inferenceensuring they run efficiently, reliably, and privately on end-user devices. Key Responsibilities Model Development & ResearchDesign, train, fine-tune, and evaluate ML models for speech recognition, generative and reasoning models, and multimodal inferenceAdapt open-source and foundation models using Hugging Face and related toolingTranslate research ideas into production-ready systems Optimization & On-Device DeploymentOptimize models for low-latency, low-power, offline executionPerform quantization, pruning, and distillationDeploy models via ONNX Runtime and OpenVINO targeting CPU, GPU, and NPU backends Systems & InfrastructureBuild pipelines for training, evaluation, benchmarking, and regression testingDefine and improve accuracy, latency, and resource metricsPartner with application and platform engineers to ensure seamless ML integrationCommunicate model performance, architectural decisions, and technical tradeoffs clearly to both technical and non-technical stakeholders Technical LeadershipOwn Cephables ML architectureSet best practices and mentor team membersEvaluate new tools, frameworks, and hardwareMentor engineers across the team on ML concepts and practices as the org grows Required Qualifications4+ years of experience in machine learning or ML systemsStrong PyTorch experienceHands-on experience with Hugging FaceProduction deployment using ONNX Runtime and/or OpenVINOExperience with acceleration frameworks like CUDA and GPU workflowsStrong software engineering skills (Python, C++, or systems-level experience)Excellent communication skills able to explain complex ML concepts, tradeoffs, and decisions clearly to engineers, product stakeholders, and non-technical partners alike Preferred QualificationsSpeech recognition or voice assistant experienceLLMs, SLMs, or reasoning modelsMultimodal ML experienceEdge or on-device AI backgroundExperience with QNN, WinML, and CoreMLAbout the TeamYou'll be joining a small, highly collaborative engineering team of engineers. You will be the dedicated ML lead there is significant greenfield opportunity here to shape systems, practices, and architecture from the ground up. Close partnership with application and platform engineers is a core part of the role.Why CephableMission-driven impact: Your models run on real devices for real users many of whom depend on Cephable as a primary way to interact with technologyGreenfield ML ownership: Shape Cephable's ML architecture from the ground up with the trust and autonomy to do it rightCutting-edge stack: On-device inference, multimodal input, NPU targeting, and privacy-first AISmall team, high trust: Work directly with senior leadership in a low-bureaucracy environmentSeed-stage momentum: Backed by top investors with enterprise partnerships at scale What we offer: Equity Meaningful equity grants (options) in a company with existing revenue and clear growth trajectoryStandard 4-year vesting with 1-year cliff Health & Wellness Health insurancemedicaldentalvision Time Off 120 hours per year accrued per pay periodUp to 40 hours carry over year to year (we want you taking vacation)8 additional hours per year of tenure15 paid Holidays11 Federal Holidays, plus,Fridays before Labor and Memorial DayExtra day for July 4thWed before and Friday after ThanksgivingLocation: Remote (Boston area preferred)
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