C++ SOFTWARE ENGINEER (PERFORM ANCE) 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 40+ filed patents.

Deep Render has recently raised its Series A

funding round from top-tier investors and is

looking to double/triple its current 20-person

team. We’re in commercial engagements with

some of the largest Big Tech companies in

the world and expect hundreds of millions of

people to use the Deep Render AI Codec by

2024.

RESPONSIBILITIES

• Work in a team to port ML research algorithms to edge devices with an

initial focus on smartphones (Android, iOS)

• Profile various algorithms to analyse performance and identify any

bottlenecks. Profiling includes data loading, data movement, data

caching, operation count, execution chipset, warm-up latency and

others

• Implement solutions to the identified bottlenecks

• Implement a high-performance entropy coding algorithm, e.g. Range

Coding or Asymmetric Numeral Systems, across different hardware

architectures

• Optional: Write custom operations using the low-level API for Android

(OpenGL ES) and iOS (Metal) systems

• Optional: Apply standard neural network runtime optimisation methods

such as pruning, low-bit quantisation, architecture tuning, batching and

others

MUST HAVE

• At a minimum, a Bachelor’s degree in computer science or related field

(Mathematics, Physics, Engineering)

• Expertise in C++

RECOMMENDED SKILLS

• At a minimum, 3-5 years of experience in performance optimisation

• Some experience with optimisation techniques. Examples include

SIMD (SSE, AVX), vectorisation, loop dependencies, multithreading,

multi-processor usage, and tensor cores

• Experience working in an ML focused environment or exposure to

PyTorch/TensorFlow