Deep Render is a Deep Tech startup founded to liberate the world of all bandwidth constraints by pioneering AI-Compression technology. Our compression codecs are based on a fundamental technology shift, representing over 100 years of progress in the industry.

We're leading the way in AI-Compression, having the world's first AI-Codec running in real-time on mobile devices. Our team comes with 50+ years of combined research experience with over 80+ filed patents.

Last year, Deep Render raised its Series A funding round from top-tier investors and is looking to grow its current 35-person team in 2024. We're in commercial engagements with some of the largest Big Tech companies in the world and expect hundreds of millions of people to be using the Deep Render AI Codec very soon.

Role:

Deep Render is looking for a cross platform Software Engineer to join our growing team. In this role, you'll be developing applications leveraging our AI-based compression technology. You'll collaborate with cross-functional teams to design new features. The ideal candidate will be a full stack developer with cross platform development experience on target ecosystems such as iOS, MacOS, Android, Windows and Linux

Responsibilities:

• Design, develop, and maintain applications that leverage Deep Render's AI-based compression technology.
• Collaborate with cross-functional teams to define, design, and ship new features.
• Develop internal tooling to improve development efficiency and support operational tasks.
  
  

Must have:

• Demonstrated expertise in C++ development, ideally using frameworks such as QT, React Native, Electron
• Familiarity with target ecosystems with experience using their native programming languages (Swift/Java/Kotlin)
• Experience in developing internal tooling or automating workflows to enhance development efficiency and operational support.
• Exposure to conducting code reviews, providing constructive feedback, and fostering a culture of knowledge sharing and best practices adherence
  
  

Preferred skills:

• Experience developing video based applications using either FFMPEG, GStreamer or equivalent library
• Familiarity with machine learning ecosystem and optimisation of machine learning inference.
• Contributions to open-source projects or a strong portfolio of relevant projects.