Machine Learn Engineer, Video Generation
- Unith
Job Description
🎥 Machine Learn Engineer, Video Generation
Remote/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 Do
Production Engineering (Core Focus)
- Own production video synthesis services and deploy/optimize models for real-time performance
- Reduce inference latency to meet a <2-second target for streaming conversations
- Monitor and improve video quality metrics and debug production issues
- Implement model versioning, A/B testing, and safe rollback procedures
Integration & Optimization
- Act as the bridge between AI research and production systems
- Integrate new models into the existing pipeline
- Design video synthesis APIs (gRPC, REST) and work with event-driven architectures
- Optimize GPU utilization, implement caching strategies, and collaborate on service orchestration
- Handle TTS integration services (Voice Connectors)
Feature Development
- Implement new visual features (expressiveness, movement, lip-sync improvements)
- Support avatar customization capabilities
- Production research enhancements into the real-time video pipeline
🧰 Tech Stack
- Python, PyTorch, AWS, Docker, Kubernetes, GPU instances
- gRPC services for streaming synthesis
- S3, Redis, RabbitMQ
✅ What We’re Looking For
Must-Have
- 3–5 years of experience deploying ML/CV models to production (not just training)
- Strong hands-on experience with PyTorch or TensorFlow
- Practical optimization experience (quantization, pruning, model serving, GPU resource management)
- Experience with video generation or real-time video processing and latency/quality trade-offs
- Strong 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 teams
Nice-to-Have
- Experience with audio-driven avatars, face reenactment, GANs, Diffusion Models, or NeRFs
- gRPC, RabbitMQ, Go, or video streaming protocols (HLS, WebRTC)
- Publications or open-source contributions in computer vision
🎯 What Success Looks Like
First 6 months - Ownership of core synthesis services with improved reliability and monitoring
- Successful deployment of at least one research model into production
- Measurable improvements in latency or video quality
First 12 months - Streaming video delivery with 30–50% latency reduction
- Production rollout of visual improvements (expressiveness, movement)
- Recognized as the go-to production ML expert bridging research and deployment
💼 What We Offer
Compensation & Flexibility
💰 Salary: €45,000 – €55,000, depending on experience
🏠 Hybrid work in Barcelona or remote options within Europe
Impact & Growth
- End-to-end ownership of critical production systems
- Unique role bridging cutting-edge CV research and real-world deployment
- Challenging problems in real-time ML, latency optimization, and scalability
- High-impact work in a small, senior team (12 people)
- Opportunity to shape ML infrastructure as the company scales
Additional Perks
🏙️ Office in the center of Barcelona
🌍 Work from anywhere
🍽️ Lunch compensation when in the office
🩺 Private health insurance with Alan
🚍 Travel allowance (for team members living 10km+ from the office)
🧾 Flexible benefits (tax-free under Spanish legislation)
🏋️ ClassPass discount
📩 How to Apply:
Submit:
- Your CV highlighting ML production experience
- A short motivation (3–5 sentences) covering: - Your experience deploying CV/video models to production
- One project where you reduced inference latency
- Why digital humans excite you
Apply via the Easy Apply button, or reach out directly to [email protected] — creativity is welcome 🤖
🔍 Recruitment Process
1. Technical interview with the tech team (60 min)
2. Small take-home assignment
3. Assignment review (60 min)
4. Reference check
5. Call with Joyce (30 min)
⏱️ Timeline: 2–3 weeks from application to offer
Ready to make digital humans faster, better, and more reliable?
👉 Apply now
