DescriptionHybrid 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 45k65k
Why this role is exciting: Youll 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 were 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.
Were looking for an experienced Production ML Engineer to take ownership of our video synthesis pipeline. This is a hands-on production-focused role where youll bring AI research to life at scale.
Youll 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.
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
- Productionize research enhancements into the real-time video pipeline
- Python PyTorch AWS Docker Kubernetes GPU instances
- gRPC services for streaming synthesis
- S3 Redis RabbitMQ
Must-Have
- 35 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
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 3050% latency reduction
- Production rollout of visual improvements (expressiveness movement)
- Recognized as the go-to production ML expert bridging research and deployment
Compensation & Flexibility
Salary: 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
Submit:
- Your CV highlighting ML production experience
- A short motivation (35 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 creativity is welcome
1. Intro call with Joyce (30 min)
2. Technical interview with Head of Engineering team (90 min)
3. Team meeting with backend & research (60 min)
4. Small take-home assignment
5. Reference check
Timeline: 23 weeks from application to offer
Ready to make digital humans faster better and more reliable
Apply now
Required Experience:
IC
Description Video Synthesis EngineerHybrid Tech Team Full-time Barcelona SpainIn a few wordsOwn and scale real-time video synthesis for lifelike digital humansProduction-first ML role bridging research deploymentFocus on latency quality and reliability at scale Barcelona (hybrid) or remote in Eu...
DescriptionHybrid 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 45k65k
Why this role is exciting: Youll 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 were 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.
Were looking for an experienced Production ML Engineer to take ownership of our video synthesis pipeline. This is a hands-on production-focused role where youll bring AI research to life at scale.
Youll 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.
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
- Productionize research enhancements into the real-time video pipeline
- Python PyTorch AWS Docker Kubernetes GPU instances
- gRPC services for streaming synthesis
- S3 Redis RabbitMQ
Must-Have
- 35 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
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 3050% latency reduction
- Production rollout of visual improvements (expressiveness movement)
- Recognized as the go-to production ML expert bridging research and deployment
Compensation & Flexibility
Salary: 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
Submit:
- Your CV highlighting ML production experience
- A short motivation (35 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 creativity is welcome
1. Intro call with Joyce (30 min)
2. Technical interview with Head of Engineering team (90 min)
3. Team meeting with backend & research (60 min)
4. Small take-home assignment
5. Reference check
Timeline: 23 weeks from application to offer
Ready to make digital humans faster better and more reliable
Apply now
Required Experience:
IC
View more
View less