Applied AI Engineer
Description For Applied AI Engineer
At Improbable, we've been venturing into unexplored territory for over a decade, seeking new ways to connect people and amplify their lives. We're shaping virtual worlds of unprecedented scale for the gaming, web3, and related sectors, creating world-changing technology from Morpheus to M2. We are growing an engineering team which specialises in deep technical problem spaces, from high performance computing to the application of AI.
As an Applied AI Engineer at Improbable, you'll work on cutting-edge AI technology to solve real customer problems. You'll develop infrastructure and pipelines for AI-powered systems, optimize AI models, and stay current with the latest AI developments. This role offers the opportunity to work on innovative projects like Somnia, the world's highest throughput EVM-based L1 blockchain, and Morpheus-related virtual events technology.
The ideal candidate has experience with modern generative AI models, data engineering practices, and a broad understanding of AI model capabilities and limitations. Professional software engineering experience, high productivity, and strong communication skills are essential.
Improbable offers a flexible work environment, with options for remote, hybrid, or in-office work at their Spitalfields, London location. The company is committed to fostering a diverse and inclusive workplace where people can do their best work and feel like they belong.
Join Improbable to tackle questions that no one else is asking and find answers that define the future in the exciting field of applied AI.
Responsibilities For Applied AI Engineer
- Work directly with modern cutting edge AI technology to solve real customer problems
- Develop infrastructure and pipelines that support the scaling and efficiency of AI powered systems
- Optimise the use of AI models, balancing accuracy, speed, and efficiency
- Stay abreast of the latest developments in the AI space
Requirements For Applied AI Engineer
- Direct experience building applications and integrations with modern generative AI models (e.g. LLMs)
- Understanding of data engineering practices and proficiency in handling data pipelines for advanced AI applications
- A broad and up to date understanding of the tradeoffs, capabilities and limitations of different available models
- Professional software engineering experience
- Ability to drive an outcome and unblock yourself and those around you with high productivity
- Ability to work independently and in a team environment
- Strong verbal and written communication skills
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