Data Scientist – Computer Vision & Machine Learning

Key Responsibilities

Advanced Computer Vision Development:

• Object Detection & Localization:Design, build, and deploy models using cutting-edge techniques likeYOLOfor object detection and localization.
• Image & Video Captioning/Tagging:Develop systems for generating descriptive captions and tags using models likeRAMandFlorence 2.
• Embedding Techniques:Implement techniques for image and video embeddings to support tasks likesimilarity searchandrecommendation systems.
• Asset Fingerprinting (Bonus):Research and develop fingerprinting techniques for uniquely identifying and tracking visual content.

Data Modeling & Semantic Analysis:

• Build multi-modal data models tointegrateandsemantically understandvisual data.
• Develop components that supportsemantic similarityandsearch/retrievaltasks based on visual inputs.

Engineering & Deployment:

• API Development:Create robust APIs and scalable solutions usingFastAPI,Docker, andAzure.
• Deployment:Lead projects from proof-of-concept toproduction-ready deployment.

Green Field Innovation:

• Innovate in areas with vague oropen-ended specifications, turning abstract ideas into concrete, scalable solutions.

Software Design Patterns:

• Implement and advocate for standard design patterns (e.g.,ports and adapters,provider patterns) to ensure system scalability and reliability.

Data Source Integration:

• Interface with various data sources to build comprehensive solutions tailored for visual data.

Required Skills & Experience
Expertise in Computer Vision:

• Proven experience inobject detection,localization,image/video captioning,tagging, andembedding.
• Familiarity with state-of-the-art models such asYOLOfor object detection and frameworks likeRAMandFlorence 2for captioning and tagging.
• Expertise inasset decomposition-extracting structured and semi-structured representations for downstream tasks (e.g.,vector search, querying).
• (Bonus)Experience inasset fingerprintingtechniques.
• Proficiency in popularcomputer visionframeworks likeOpenCV,TensorFlow, andPyTorch.

Bonus Skills
Graph Machine Learning:

• Experience withGraph Neural Networks(GNNs) and othergraph-based machine learning techniques.

Agentic Applications:

• Familiarity with frameworks foragentic applicationslikeCrew,Autogen, andPydantic AI.

Role Expectations

This is a leadership role ideal for someone eager to push the boundaries ofcomputer vision, innovate across multiple projects, and drive initiatives from conception to deployment. If you are a visionary in the field ofcomputer visionandmachine learning, this position offers you the opportunity to lead cutting-edge projects in a fast-paced, innovative environment.

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