We are looking for a Fullstack Software Engineer to join our team and help build robust,
scalable systems that bring our state-of-the-art generative AI systems to the wider audience.
This fullstack role has a strong backend emphasis, requiring deep experience in server-side
architecture, API design, distributed systems, and frontend frameworks, along with a solid
engineering mindset and the ability to work cross-functionally with ML engineers, product,
research, and creative teams. As a member of our fullstack engineering team, you’ll shape
core infrastructure, set best practices, communicate with stakeholders and mentor your
peers.
Key Responsibilities
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Design and implement scalable backend architectures for AI-powered creative tools
and workflows. -
Build high-performance APIs and microservices that handle generative AI
inference/training and video/audio processing. -
Design and implement user interfaces that make complex generative AI capabilities intuitive and accessible.
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Develop robust data pipelines for ingesting, processing, and storing large-scale media content.
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Design and maintain database schemas, caching layers, and data storage solutions for multimedia content.
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Build authentication, authorisation, and security systems for enterprise-grade applications.
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Optimise backend performance for low-latency AI inference and high-throughput media processing.
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Integrate backend systems with ML training and inference pipelines.
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Implement monitoring, logging, and alerting systems for production backend services.
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Collaborate with ML engineers to optimise model serving and deployment infrastructure.
Must Haves
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5+ years of experience in fullstack software development.
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Strong expertise in server-side programming languages (we use Python).
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Proven experience designing and implementing RESTful APIs and microservices
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architectures.
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Proficiency in modern JavaScript/TypeScript and at least one major frontend
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framework (React, Vue.js, or Angular).
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Deep understanding of database design, optimisation, and management
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(PostgreSQL, Neo4j, Redis).
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Experience with cloud platforms (AWS, GCP, Azure) and infrastructure as code
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(Terraform).
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Proficiency with containerisation and orchestration technologies (Docker,
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Kubernetes).
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Strong knowledge of distributed systems, message queues, and event-driven
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architectures.
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Experience with high-performance computing, parallel processing, and optimisation
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techniques.
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Familiarity with CI/CD pipelines, automated testing, and DevOps practices.
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Understanding of system design principles, scalability, and performance optimisation.
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Experience with caching strategies, load balancing, and CDN implementation.
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Experience with CSS frameworks and responsive design.
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Strong problem-solving skills and attention to detail.
Nice to Have
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Experience with ML and/or computer vision frameworks like PyTorch, Numpy or
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OpenCV.
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Knowledge of ML model serving infrastructure (TensorFlow Serving, TorchServe,
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MLflow).
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Knowledge of WebGL, Canvas API, or other graphics programming technologies.
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Familiarity with big data technologies (Kafka, Spark, Hadoop) and data engineering
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practices.
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Background in computer graphics, media processing, or VFX pipeline development.
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Experience with performance profiling, system monitoring, and observability tools.
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Understanding of network protocols, security best practices, and compliance
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requirements.
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Open-source contributions or technical writing experience.
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Entrepreneurial mindset or experience working with startups or fast-paced teams.
