3dEYE is a leading pure cloud video AI analytics monitoring platform that requires no additional server or bridge purchase. 3dEYE platform is camera-agnostic and includes an administration, live video monitoring, video management portal, AI-powered analytics, and billing portal. With 3dEYE, systems integrators, IT companies, and telcos can create their own turn-key business and offer cloud VSaaS solutions instantly. The platform enables users to deploy multi-site cloud-based live video monitoring and connect tens of thousands of cameras in a matter of days.

By leveraging the power of AI analytics and AWS cloud processing benefits, 3dEYE offers top security, reliability, redundancy, minimum latency, unlimited scalability, and cost-effectiveness. We envision a future where security operations are proactive, leveraging cutting-edge technology to ensure safety, efficiency, and rapid response. We aim to empower security professionals with seamless web tools, proactive AI-driven security measures, and advanced automation workflows for smarter live video monitoring and investigations.

Role Description

3dEYE Inc. is seeking a highly skilled Data Scientist to join our team. This full-time, remote role will focus on developing, training, and testing machine learning models and creating innovative algorithms for our AI-powered video surveillance solutions. As a Data Scientist at 3dEYE, you’ll be responsible for advancing the accuracy, efficiency, and scalability of our analytics models, ensuring they meet the needs of high-performance, real-time applications.

The ideal candidate will have extensive experience with machine learning model development and deployment, a strong foundation in data science, and proficiency in model training frameworks and tools. This role offers the opportunity to collaborate with engineering and product teams to build cutting-edge AI-driven features.

Key Responsibilities

Design and implement machine learning models for video analytics, including model training, testing, and evaluation.
Develop and fine-tune algorithms to improve model accuracy and computational efficiency.
Leverage large datasets to create innovative solutions that support complex analytics like object detection, face recognition, and people counting.
Collaborate with cross-functional teams to integrate models into production environments and continuously optimize them for performance.
Monitor model performance, retraining as needed to maintain high accuracy and reliability.
Research and implement the latest techniques and tools in machine learning to stay ahead in the field.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
5+ years of experience in data science, machine learning, or a related field, with proven experience in model development, training, and testing.
Track record of developing successful machine learning models in production environments.
Proficiency in Python and machine learning frameworks, including PyTorch, TensorRT, and ONNX.
Experience with CUDA for GPU-accelerated computing.
Deep Learning & CV Frameworks:

- CNNs & Vision Transformers (ViT): Building and optimizing detection/segmentation/classification models, with experience fine-tuning for video analytics use cases (e.g., object tracking, activity recognition).

LLM & Agent Integration:

- LLMs: Experience in fine-tuning, RAG pipelines, and embedding-based retrieval for multimodal context.

- Multimodal AI Agents: Building systems that combine vision-language models (VLMs) with LLMs for tasks like video Q&A, summarization.

AI Agents & MCP: Familiarity with deploying AI agents (self-driving workflows, autonomous decision-making) and frameworks such as LangChain or custom multi-agent setups.
Familiarity with cloud-based services (e.g., AWS) and deploying models in cloud environments.

Additional Qualifications

Strong analytical and problem-solving skills, with an innovative approach to developing complex algorithms.
Excellent communication skills to collaborate with cross-functional teams.
Proactive in staying updated on advancements in machine learning and AI.

Preferred Qualifications: