Software Engineer: Computer Vision & Deep Learning Ref 2022/0002/001 (closed)
Salary Market Aligned
Location Singapore
Consultant Jun Lim (R1329913)
Job Ref 2022/0002/001
Date Posted 25 February 2022
Our client is a rapidly growing organisation focused on end-to-end AI engineering. Over the next few years, the Firm is focused on building a vast array of hardware and software products to cater to the growing demand for computer vision and AI applications in Smart Cities, Industry 4.0, defence and medical areas.
Headquartered in Europe, the Firm has clients across the European Union, Middle East, and India. It has operations throughout Asia and Europe and continues to expand globally.
The Role
The Firm is looking for a Software Engineer: Computer Vision & Deep Learning to be a part of its world-class team. In this role, you will develop scalable computer vision and deep learning approaches for resource-constrained edge devices and single/multi-node server-side deployment. You will collaborate with various team members to identify needs and deliver new capabilities for Computer Vision and Deep Learning-based solutions.
Key Responsibilities
Build state-of-the-art high performing low latency computer vision and deep learning applications on resource-constrained edge devices
Train, fine-tune, optimize, and customise perception DNNs in low precision (FP16/INT8) across multiple GPUs, including but not limited to object detection, segmentation, anomaly detection, activity recognition, and NLP-based image search
Suggest, collect, synthesise requirements and data to create an effective feature roadmap
Optimise deep neural networks and the associated pre/post-processing to run efficiently on edge devices
Apply low precision inference, quantisation, and compression of DNNs
Improve DNN architectures using ML algorithms on custom deep learning accelerators
Continuously improve inference latency, accuracy, and power consumption of DNNs
Develop and integrate functional and performance models of accelerators
Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas to improve DNNs
Collaborate across the company to guide the direction of computer vision and deep learning inferencing, working with software, research, and product teams
Key Requirements
Masters with 4+ years or PhD Degree with 2+ years of industry experience in one or more of the following areas: Deep Learning, Computer Vision, Computer Science, Computer Architecture, Electrical, and Computer Engineering, or related technical field or equivalent experience
Proficiency with CV & DL modeling frameworks. (e.g. OpenCV, PyTorch, TensorFlow, Keras, Caffe, ONNX, etc.)
Industry experience in the collection, cleaning, and processing of data
Expert knowledge in designing and training computer vision and deep learning models in Python or C++
Solid fundamental computer vision, image processing, and deep learning methods and concepts
Experience with using Linux based operating systems, Git, and Docker
Strong overall software engineering skills with the ability to deliver clean, well-tested code
Deep knowledge of math, probability, statistics, and algorithms
Ability to work as a member of a team, while also being able to work independently, define goals, scope, and lead your own development effort
GStreamer and Deepstream knowledge is a bonus
Why Join the Firm
Be a part of a people-first company that nurtures and rewards employees
The best place to work on cutting-edge technologies and innovative products
Fast moving, challenging, and unique business problems
Flat organisation and commitment to personal development
Diverse work environment and highly collaborative team ethics
Opportunities for international relocation and transfer
Competitive salary and rewards
If you are interested to work at the cutting edge of technology for a high-growth organisation, we would like to talk to you.
Please click the APPLY NOW button and indicate your notice period in your CV. Data provided is for recruitment purposes only.
We thank you for your interest in this position and regret that only shortlisted candidates will be notified.