Technology
Computer Vision Engineer (Intern)
Location: Bengaluru | Full Time
About Us:
What about somewhere with incredible and diverse career and development opportunities where you can truly discover your passion? Are you looking for a culture of openness, collaboration, and trust where everyone has a voice? What about all of these? If so, then Stylumia could be your next career challenge. Working with cutting-edge technologies in Computer Vision, Natural Language Processing and witnessing them play out in real-world applications. Stylumia is a one of its kind actionable intelligence platform using Artificial Intelligence, enabling fashion and lifestyle businesses to make informed decisions. The business impact areas are revenue, profit, working capital, and consumer loyalty. We are a B2B SaaS business, powering fashion and lifestyle brands and retailers globally including the Fortune 100. We have won a few prestigious awards including the Amazon AI Conclave award 2019 (Retail), Nasscom Emerge 50, YourStory Techsparks TECH30, and Circular Change Maker award 2019 to name a few. We are also recognized by the United Nations and Fashion For Good for contributing to sustainability globally in the fashion & lifestyle industry. Join us, not to do something better, but to attempt things you never thought possible.
About the Team:
The Data Science team is one of Stylumia’s important arms in ensuring we develop cutting-edge prediction algorithms defining the future of fashion.
You will get to work with the best data science minds including advisory from the world’s first 4x Kaggle grandmaster.
As a Computer Vision Engineering Intern, you will be responsible for the Neural network workload analysis and modeling of AI accelerators and testing.
Job Description:
- Stylumia’s Consumer Intelligence Tool understands True Demand and provides insights to the customers. “An Image is Worth 16×16 Words” – There is a lot of information hidden in images. Your job will be to extract as many insights as possible from the data.
- As a Computer Vision Engineer, you’ll be working on several areas like Visual Recognition, Segmentation, Feature Extraction/Representation Learning, Generative Learning (for example GANs), etc.
- At Stylumia, you’ll get your hands on millions of images and respective text data. Your job is to use this data and extract information from the data.
- Work within the Engineering Team to design, code, train, test, deploy, and iterate on enterprise-scale machine learning systems.
- At Stylumia, you’ll get good support and freedom to research and experiment.
Responsibilities:
- As a Computer Vision Engineer, you’ll be responsible for creating image-based deep learning systems and making them production ready.
- You will work with various stakeholders to understand their business requirements. Formulate the appropriate predictive solutions leveraging statistical and machine learning tools.
- Prioritizing tasks and taking ownership of efficiently managing project timelines and deliverables.
- Help shape the product roadmap and execute the modeling at scale.
- Researching on SOTA models and implementing the models on the current data.
- Collaborate with a cross-functional team to integrate computer vision technology into products and services.
Requirements and Qualifications:
- A Bachelor’s/Master’s degree in Computer Science, Information Technology, Electrical Engineering, Statistics, or related field.
- Eligible batches: 2022 and 2023 passouts.
- A deep understanding of computer vision, machine learning, and deep learning concepts and the ability to improve current models through finding the right area of improvement.
- Strong problem-solving skills with the ability to think from the first principles.
- Strong proficiency in Python.
- Experience in any one of the deep learning frameworks like Pytorch/Tensorflow.
- A thorough understanding of the mathematics behind the various deep learning algorithms.
- Preferred skills, but not a must-have
- Worked on projects that involved multimodal machine learning (for example, text+image classification).
- Worked on projects that included feature extraction from images and a good understanding of clustering and distance metrics.
- Experience in Self-Supervised and Semi-Supervised learning.
If you are someone who is passionate about AI and has a strong desire to work in a fast-paced, dynamic environment, with an ability to demonstrate ownership capabilities, we strongly encourage you to apply.
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