Computer Vision and Deep Learning Software Engineer

Key Skills

Java Programming, Python Programming, Ruby on Rails, Mechanical, Java Programming, Unix Operating system, logo, Offshore,

Job Description

As a Software Engineer you will be a member of the Deep Learning team at Rivian, which develops advanced machine learning algorithms that directly impact safety critical self-driving features of our category defining vehicles.

As a member of the team, you will be working with business partners, software development engineers, testers and UI/UX designers to design, implement, test, launch, document, and maintain complex software applications, tools, and systems. You will have a significant influence on our overall strategy by helping define how our in-cabin systems communicate and capture the customer journey. We are at the center of the infotainment experience. You will learn a variety of cutting-edge technologies, development processes, and develop well-rounded skills in leadership and design.

We are looking for 10+ engineers to join our ADAS team in Serbia.

Responsibilities

• Develop, optimize and deploy ultra-low latency Deep learning/ Machine Learning algorithms for Rivian ADAS use cases.
• Research state of the art model compression and efficient model design techniques and enable the team to leverage these across a wide range of customer facing features.
• Collaborate with the low-level software and hardware architecture teams to characterise the in-house ML models on our embedded platforms and optimize the models subject to the on device compute and memory constrains.

Requirements

• Preferred BSc. in Computer Science, Electrical, Mechanical, Aerospace Engineering or a related field.
• Good understanding of the fundamentals of deep learning with 3+ years of industrial experience.
• Research and development experience in one or more of the following areas:
• Model compression and neural architecture search techniques
• Knowledge distillation, pruning, quantisation and quantisation aware training
• Optimising and deploying inference on various embedded processors
• Experience defining compute architecture for efficient Deep learning inferencing
• Capability to understand hardware spec documents and performance profiling tools
• Strong Python programming background and in-depth knowledge of at least one framework amongst PyTorch, TensorFlow or MXNet
• Familiarity with DL model optimisation strategies such as pruning, knowledge distillation, training time and post training quantisation
• Ability to work in a fast-paced development environment
• Good team player with great communication skills to drive cross functional efforts
• Passionately motivated to take ideas from R&D phase to a product
• Productisation of inference models on embedded platforms.
• Experience with training and deploying deep learning models computer vision such as object detection and segmentation.
• Experience designing and deploying automotive grade applications
• Experience with software development process for safety critical systems (ISO 26262)
• Experience implementing inference logic from first principles using low level subroutines like BLAS, CUDA Kernels or C++ natively.