Sign up with

Already have an account? Log in here

Need some help?
Talk to us at +91 7670800001

Machine Learn Engineer, Video Generation at UNITH

Barcelona, Catalonia, Spain -

Full Time

Start Date

Immediate

Expiry Date

12 May, 26

Salary

55000.0

Posted On

11 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Video Generation, Production Engineering, Python, PyTorch, AWS, Docker, Kubernetes, Real-Time Systems, Computer Vision, Model Optimization, Debugging, API Design, Latency Optimization, Video Processing, Collaboration

Industry

Software Development

Description

🎥 Machine Learn Engineer, Video Generation Hybrid · Tech Team · Full-time 📍 Barcelona, Spain In a few words Own and scale real-time video synthesis for lifelike digital humans Production-first ML role bridging research → deployment Focus on latency, quality, and reliability at scale 📍 Barcelona (hybrid) or remote in Europe | 💰 €45k–€55k Why this role is exciting: You’ll work on cutting-edge digital human technology where your production optimizations have immediate, visible impact on real users and global enterprise customers. 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, redefining how businesses interact with customers worldwide. 🚀 The Role We’re 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’ll work at the intersection of computer vision, ML infrastructure, and real-time systems, ensuring our digital humans run reliably, efficiently, and with ultra-low latency — without sacrificing visual quality. 🛠️ What You’ll DoProduction Engineering (Core Focus) Own production video synthesis services and deploy/optimize models for real-time performance Reduce inference latency to meet a

Responsibilities

The role involves owning and scaling real-time video synthesis for lifelike digital humans, focusing on production engineering and optimizing models for performance. You will integrate new models into the existing pipeline and ensure reliable, efficient operation with low latency.