Full-time | Tech TeamBarcelona (hybrid) or remote within Europe€45,000 – €55,000

Si desea saber un poco más sobre esta oportunidad, o está considerando presentar su candidatura, por favor, lea la siguiente información del puesto.

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.

In a nutshellOwn 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

Why this role stands outThis 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 general enterprise customers. The problems are hard, the constraints are real, and the work goes far beyond experimentation or demos.

The RoleWe'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.

Production Engineering (Core Focus)

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

Feature Development

Productionise visual improvements (expressiveness, motion, lip‐sync)

Support avatar customisation and identity preservation

Turn research prototypes into robust, real‐time features

Python, PyTorch

AWS, Docker, Kubernetes, GPU‐backed instances

gRPC for streaming services

What We're Looking ForMust-have

3–5 years' experience deploying ML / CV models into production

Strong hands‐on experience with PyTorch or TensorFlow





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

Nice‐to‐have

Experience with audio‐driven avatars or face animation

GANs, Diffusion Models, NeRFs, or related CV techniques

Open‐source contributions or publications in computer vision

What xhfqzwm Success Looks LikeFirst 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

What's on OfferCompensation & FlexibilityHybrid working in Barcelona or remote within Europe

Impact & GrowthEnd‐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

Versátil working arrangements

Private health insurance

Commuter / travel allowance

Flexible benefits under local tax scheme

📌 Machine Learning Engineer – Real-Time Video Generation (Barcelona)
🏢 threesixfive
📍 Barcelona