Job Description

Location Singapore, North East

Planning Area
ANG MO KIO

Job Type
Permanent

Salary
$6,500 - $9,500 Per Month

Date Posted
8 hours ago

Expiry Date
18-Aug-2022
Additional Details


Job ID
317331

Job Views
1

Roles & Responsibilities We are looking for a Machine Learning Lead to be part of our AI-Video Analytics team, who is passionate about building products that the customers love. You will join a dynamic and fast-paced environment and work with our product development team to design, build and roll-out our "Deep Learning enabled" Video Analytics Software suite that delivers STEngg's vision and strategy in this domain. In this role, you will have a sharp focus on product offerings from the deep learning perspective, and utilize your knowledge to solve real-world video analytics problems from a machine learning perspective. You will be expected to deliver solutions that can be deployed to scale and deployed to last, and make justified decisions based on that. Our product development team has demonstrated its ability to create innovative solutions in the area of video analytics, and we are poised for the next phase of growth and expansion. Responsibilities:

• Collaborate with product managers, software engineers, and data scientists to conceptualize, research, design, and build high-performance, low latency, and scalable machine learning solutions.
• Take ownership of the team’s machine learning models and keep track of their full lifecycle by ensuring they are up to date and applying continuous improvement.
• Make and justify choices with regards to throughput, latency and cost, in the addition of machine learning models.
• Work with the Application team to implement and optimize these models for deployment with awareness in hardware acceleration.
• Develop tooling and processes to accelerate and standardize machine learning workflows.

• Bachelor's Degree in Computer Engineering or related technical discipline.
• Knowledge in deep learning frameworks. (Tensorflow, PyTorch, Mxnet, Scikit-learn, Numpy, Pandas, etc)
• Industry experience using MLOps and ML lifecycle management platforms such as MLFlow, KubeFlow, AirFlow, AWS Sagemaker, Azure ML, etc.
• Experience using Docker and Kubernetes.
• Familiar with one or more model serving frameworks. (Tensorflow Serving, TorchServe, NVIDIA Triton Inference Server)
• Strong problem solving, analytical and conceptual skills, with good communication skills
• Able to work independently with minimum guidance and monitoring, a good team player

• Experience in GPU servers, and NVIDIA development stack. (CUDA, Deepstream, TensorRT, Nvidia-docker, etc)
• Experience in building and optimizing high throughput video processing pipelines.
• Experience in distributed databases or systems. (Hadoop, Spark, MinIO)
• Experience in message queuing protocols. (Kafka, MQTT, RabbitMQ, AMQP)
• Experience in software packaging, deployment, UAT, and production.