![Deep Render](https://media.trabajo.org/img/noimg.jpg)
Lead C++ Engineer
4 weeks ago
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:
Join our team as a Lead C++ Engineer and lead a team of six Performance Engineers. You will play a pivotal role in the development and implementation of a cutting-edge video codec, optimising for speed and efficiency. With a focus on C++ programming, your team will tailor solutions to specific chipsets, enhancing our technological capabilities. As a key figure in the Engineering team, you will collaborate extensively with Senior Leadership to influence our product development and cultivate our company culture.
Responsibilities:
- Provide technical leadership and strategic direction for the development and deployment of our flagship DR codec.
- Engage in hands-on C++ development to adapt our model for optimal performance.
- Manage and mentor a team of up to six Performance Engineers, working in partnership with the People Team to promote professional growth and team effectiveness.
Must Have:
- Degree in Computer Science, Engineering, or a related field is preferred; relevant experience may be considered as an alternative.
- Demonstrated expertise in C++ development, with a proven track record in technical leadership and performance optimisation.
- Experience in managing technical teams, including conducting one-on-one meetings, performance evaluations, and supporting career development and mentoring.
Preferred Skills:
- Knowledge of ML accelerator technologies (GPU, NPU) and their ecosystems.
- Experience in video compression techniques.
- Familiarity with deploying ML models on resource-constrained devices.
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