OpenCv and Perception Engineer

Flam is seeking an experienced Perception engineer that is passionate about building mobile applications. Our vision is to build a platform that enables shared experiences among billions of users. This is what’s known as the metaverse: a persistent space where anyone can do just about anything they can imagine, from anywhere in the world and on any device. The breadth of opportunities, and the evolving demands of this first-of-its-kind platform, ensure that your avenues for growth are always expanding and flexible. We are looking for candidates with at least 2+ years of experience to build our perception model for mobile interface.

Responsibilities

• Develop computer vision algorithms for object detection, tracking, and classifications that are robust to lighting changes.
• Collaborate with estimation engineers and assist in developing powerful feature detectors/ descriptors.
• Stay organized and communicative with others to ensure that goals and objectives are being met on time.
• Guarantee the consistency of projects, you will participate in end-to-end development and training in Cloud to optimize development on mobile platforms.

Skills and qualification

• Expertise in one or more areas: Image Processing, Geometric Computer Vision, Deep Learning (ideally CNNs), classical machine learning such as SVM, decision trees, boosting, graphical models, sequential prediction, or sampling methods
• Expertise with one of the following DL frameworks:- Tensorflow, Keras, Caffe, Pytorch
• Proficient in OpenCV and image processing stacks.
• Experience in designing large-scale machine learning pipelines
• Domain expertise in one the areas : Social Media, product based company.
• Should have experience in Cloud,Edge and Mobile deployment architectures.
• Applying statistical and machine learning techniques, such as, mean-variance, k-means, nearest-neighbor, support vector, Bayesian time-series and network analysis to identify outliers, classify events or actors, and correlate anomalous sequences of events.
• Good knowledge of image processing fundamentals such as Filters, Homographies, Edge detection, Hough transforms.