Meta AR/VR Job | RL Machine Learning Engineer | Oculus
Citys（岗位城市）: Shanghai, China
Meta’s RL organization brings together world-class experts to develop and ship groundbreaking products at the intersection of hardware, software, and platform.
Technical Operations team has the responsibility for evaluating technologies and identifying supply chain solutions that allow RL Org to deliver products to market at scale. Hardware Test Engineer drive the development and deployment of manufacturing hardware test systems. You as machine learning engineer within hardware test engineering will help design machine learning model with manufacturing test dataset and ensure the model exhibit super performance vs human or traditional test metrology.
You must be responsive, flexible and able to succeed within an open collaborative peer environment. We are looking for someone with a productive mindset who can apply his/her expertise to solve problems in creative, insightful ways.
This position is full-time and based in China (Shanghai or Shenzhen).
BS or MS degree in Computer Science or related field
3+ years of experience in building machine learning system
Experience with at least one of major machine learning frameworks
Experience in one or both of the following areas: object detection, audio classification
Intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques and their performance characteristics
Strong programming skills in Java, Python, or C++
Ability to fast adapt to new technology, concept, approaches, and environment, with a learning attitude and improvement mindset. Self driven for problem-solving
Develop machine learning models with manufacturing test dataset(image, audio file..etc)
Evaluate and optimize model to ensure their effectiveness and performance
Design machine learning infrastructure to continue scale in future
Extensive knowledge in deep learning and computer vision techniques
Proficiency in Python and experience with PyTorch or TensorFlow
Experience with server architectures, and distributed systems
Can-do attitude with the ability to drive results, motivate and collaborate with xfn teams to close issues in a timely manner
Ability to be in a leadership position and achieve results with minimal supervision
Travel required: up to 30% domestically or internationally combined