Machine Learning Engineer – Video Generation

Full-time | Tech Team
📍 Barcelona (hybrid) or remote within Europe
💰 €45,000 – €55,000

threesixfive is supporting a high-growth conversational AI company building lifelike digital humans for enterprise use cases.

Our client designs and deploys real-time, human‑like digital avatars that combine video synthesis, facial animation, voice, and conversational AI. Their technology is used by global organisations to deliver interactive customer experiences at scale, across dozens of languages and markets.

This is a technically ambitious team working at the cutting edge of computer vision, real-time ML systems, and production AI infrastructure, with a strong focus on reliability, performance, and real‑world impact.

Own and scale real‑time video synthesis systems for lifelike digital humans

A production‑first ML role
, bridging research and live deployment

Focus on latency, video quality, and reliability at scale

This is a rare opportunity to work on real‑time, user‑facing ML systems where your optimisations have an immediate and visible impact.

You’ll be part of a small, senior engineering team building cutting‑edge digital human technology used by global enterprise customers. The problems are hard, the constraints are real, and the work goes far beyond experimentation or demos.

We’re looking for an experienced Production Machine Learning Engineer to take ownership of a real‑time video synthesis pipeline.

This is a hands‑on, systems‑oriented role at the intersection of:

ML infrastructure

You’ll be responsible for taking research models and making them run reliably in production
, under strict latency and quality constraints.

• Own and operate production video synthesis services
• Deploy and optimise ML models for real‑time inference
• Reduce end‑to‑end inference latency (targeting sub‑2s streaming use cases)
• Monitor video quality and system performance; debug production issues
• Implement model versioning, A/B testing, and safe rollback strategies
• Act as the bridge between research and production systems
• Integrate new CV / video models into an existing real‑time pipeline
• Design and maintain APIs for video synthesis (gRPC, REST)
• Optimise GPU utilisation and inference throughput
• Implement caching strategies and support service orchestration
• Integrate text‑to‑speech / audio services where required

• Product ionise visual improvements (expressiveness, motion, lip‑sync)
• Support avatar customisation and identity preservation
• Turn research prototypes into robust, real‑time features
• Python
  , Py Torch
• AWS, Docker, Kubernetes, GPU‑backed instances
• gRPC for streaming services

• 3–5 years’ experience deploying ML / CV models into production
• Strong hands‑on experience with PyTorch or Tensor Flow
• Practical experience with model optimisation (quantisation, pruning, serving)
• Experience with video generation or real‑time video processing
• Solid understanding of latency vs quality trade‑offs
• Strong Python skills for backend services and ML serving
• Production infrastructure experience (Docker, cloud platforms, CI/CD)
• Strong debugging skills and ability to collaborate across teams

• Experience with audio‑driven avatars or face animation
• GANs, Diffusion Models, NeRFs, or related CV techniques
• Open‑source contributions or publications in computer vision

First 6 months

Ownership of core video synthesis services

Improved monitoring, reliability, and operational confidence

At least one research model successfully deployed into production

Measurable improvements in latency or video quality

First 12 months

Significant latency reduction in streaming video delivery (30–50%)

Production rollout of visual improvements

Recognised internally as the go‑to engineer for production ML and real‑time video systems

Hybrid working in Barcelona or remote within Europe

End‑to‑end ownership of critical production systems

Technically challenging problems in real‑time ML and scalability

High‑impact role in a small, experienced engineering team

Opportunity to influence ML infrastructure as the platform scales

Central Barcelona office

Flexible working arrangements

Private health insurance

Commuter / travel allowance

Flexible benefits under local tax schemes

Wellness and fitness discounts

To apply or learn more: email kris with your CV or Linked In profile.