CIPIO.ai
Ml Engineer (Remote)
Ml Engineer | CIPIO.ai | India
CIPIO.ai is UGC Marketing Platform propels brands ofall sizes to new heights with a robust Ad Generator and a comprehensive UGCMarketplace.
...Ml Engineer | CIPIO.ai | India
CIPIO.ai is UGC Marketing Platform propels brands of all sizes to new heights with a robust Ad Generator and a comprehensive UGC Marketplace.
We help brands transform their marketing channels, content perpetually, and scale their brand impact cost effectively.
Web-Site: www.CIPIO.ai
Job Title: ML Engineer – Computer Vision and GenAI
Job Description:
We seek a highly skilled ML Engineer specializing in Computer Vision and GenAI to join our dynamic team. As a critical member of our AI development team, you will be primarily responsible for designing, implementing, and scaling advanced algorithms for developing a Large Video Model (LVM) leveraging Generative AI techniques. Your expertise in Python programming and deep understanding of Computer Vision will be essential in pushing the boundaries of innovation in this field.
Responsibilities:
● Algorithm Development: Design, develop, and optimize cutting-edge algorithms for a Large Video Model using Generative AI techniques.
● Computer Vision Expertise: Utilize your expertise in Computer Vision to extract meaningful information from video data.
● GenAI Implementation: Implement Generative AI models to generate realistic and high-quality video content, ensuring scalability and efficiency.
● Python Development: Leverage your proficiency in Python programming to build robust and scalable software solutions, integrating AI algorithms into production systems.
● Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to deliver innovative AI-powered solutions.
● Research and Innovation: Stay up-to-date with the latest advancements in Computer Vision and Generative AI, conducting research to identify novel approaches and techniques applicable to video creation.
Requirements:
● Degree: Bachelor’s or Master’s (Preferred) in Computer Science, Artificial Intelligence, or a related field with 4+ years of experience.
● Proven Experience: Demonstrated experience in developing and deploying AI solutions, focusing on Computer Vision and Generative AI. Previous experience working on video processing algorithms is highly desirable.
● Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform for scalable AI deployments.
● Familiarity with video processing techniques and libraries such as FFmpeg, VideoLAN, or similar.
● Knowledge of software development best practices, including version control systems (e.g., Git), code review processes, and agile methodologies.
● Expertise in Python: Strong proficiency in Python programming language and libraries commonly used in AI development, such as TensorFlow, PyTorch, OpenCV, and NumPy.
● Deep Learning: In-depth understanding of deep learning techniques, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).
● Software Engineering Skills: Solid software engineering skills with experience designing, developing, and deploying production-grade software systems.
● Problem-Solving Skills: Strong analytical and problem-solving abilities, passionate about tackling complex AI challenges and driving innovation.
● Communication Skills: Excellent communication skills with the ability to effectively collaborate with team members and communicate technical concepts to non-technical stakeholders.
● Adaptability: Ability to thrive in a fast-paced and dynamic environment, with a willingness to learn new technologies and methodologies as required.
Interview Process:
- 1st Round – Technical discussion to understand your skill-set, area of expertise and interest
- 2nd Round – Assignment
- 3rd Round – Discussion with Management team in the US and India (This is generally a panel discussion; however, if in case the panelists are not available (considering they operate in different time-zones) we might require to do these interviews separately with each panelists)
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