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Video Synthesis Engineer
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Overview Full-time role based in Barcelona, Spain (hybrid) or remote in Europe. Own and scale real-time video synthesis for lifelike digital humans with a focus on latency, quality, and reliability at scale.About UNITH At UNITH, we're transforming customer journeys with conversational AI. Listed on the ASX, we create lifelike digital humans using cutting-edge synthetic facial movement, voice engineering, and conversational design. Our digital humans speak 60+ languages with 600+ voices.The Role We are looking for an experienced Production ML Engineer to take ownership of our video synthesis pipeline. This is a hands-on, production-focused role where you'll bring AI research to life at scale. You will work at the intersection of computer vision, ML infrastructure, and real-time systems to ensure our digital humans run reliably, efficiently, and with ultra-low latency — without sacrificing visual quality.What You'll Do Production Engineering (Core Focus) Own production video synthesis services and deploy/optimize models for real-time performanceReduce inference latency to meet a Monitor and improve video quality metrics and debug production issuesImplement model versioning, A/B testing, and safe rollback proceduresIntegration & Optimization Act as the bridge between AI research and production systemsIntegrate new models into the existing pipelineDesign video synthesis APIs (gRPC, REST) and work with event-driven architecturesOptimize GPU utilization, implement caching strategies, and collaborate on service orchestrationHandle TTS integration services (Voice Connectors)Feature Development Implement new visual features (expressiveness, movement, lip-sync improvements)Support avatar customization capabilitiesProductionize research enhancements into the real-time video pipelineTech Stack Python, PyTorch, AWS, Docker, Kubernetes, GPU instancesgRPC services for streaming synthesisS3, Redis, RabbitMQWhat We're Looking For Must-Have3-5 years of experience deploying ML/CV models to production (not just training)Strong hands-on experience with PyTorch or TensorFlowPractical optimization experience (quantization, pruning, model serving, GPU resource management)Experience with video generation or real-time video processing and latency/quality trade-offsStrong Python skills for backend services (FastAPI, Flask) and ML serving (TorchServe, ONNX Runtime)Production infrastructure experience (Docker, AWS, CI/CD pipelines)Strong debugging skills and ability to collaborate across research and backend teamsNice-to-HaveExperience with audio-driven avatars, face reenactment, GANs, Diffusion Models, or NeRFsgRPC, RabbitMQ, Go, or video streaming protocols (HLS, WebRTC)Publications or open-source contributions in computer visionWhat Success Looks Like First 6 months - Ownership of core synthesis services with improved reliability and monitoringSuccessful deployment of at least one research model into productionMeasurable improvements in latency or video qualityFirst 12 months - Streaming video delivery with 30-50% latency reductionProduction rollout of visual improvements (expressiveness, movement)Recognized as the go-to production ML expert bridging research and deploymentWhat We Offer Compensation & Flexibility€45,000 - €65,000 depending on experienceHybrid work in Barcelona or remote options within EuropeImpact & GrowthEnd-to-end ownership of critical production systemsUnique role bridging cutting-edge CV research and real-world deploymentChallenging problems in real-time ML, latency optimization, and scalabilityHigh-impact work in a small, senior team (12 people)Opportunity to shape ML infrastructure as the company scalesAdditional Perks Office in the center of BarcelonaWork from anywhereLunch compensation when in the officePrivate health insurance with AlanTravel allowance (for team members living 10km+ from the office)Flexible benefits (tax-free under Spanish legislation)ClassPass discountHow to Apply Submit:Your CV highlighting ML production experienceA short motivation (3-5 sentences) covering: your experience deploying CV/video models to productionOne project where you reduced inference latencyWhy digital humans excite youApply via the Easy Apply button, or reach out directly to — creativity is welcomeRecruitment Process Intro call with Joyce (30 min)Technical interview with Head of Engineering + team (90 min)Team meeting with backend & research (60 min)Small take-home assignmentReference check⏱️ Timeline: 2-3 weeks from application to offerReady to make digital humans faster, better, and more reliable?Apply now#J-18808-Ljbffr
