Job Description for Computer Vision Research Engineer

Core Responsibilities :

- Architect and develop novel Deep Learning (DL) and Machine Learning (ML) neural network architectures, including those for generative AI.

- Design, develop, and refine Vision-Language Model (VLM) architectures, and integrate them with generative AI techniques for advanced multimodal understanding and generation.

- Spearhead the New Product Development (NPD) process, delivering innovative, differentiated products/solutions that provide distinct consumer advantages and exceed market benchmarks.

- Engineer and implement advanced computer vision and deep learning algorithms to resolve intricate scene understanding challenges and their multimodal interpretations.

- Evaluate experimental visual and contextual data to discern and execute performance enhancement strategies.

- Facilitate the transition of algorithms into operational prototypes and/or real-time system demonstrations.

- Establish and manage a cohesive team of resources to ensure seamless integration with related functions.

Job Requirements:

- B.Tech in AI and Computer Science, Engineering, or a related discipline.

- 1-5 years of experience in computer vision, Generative AI, Vision Language Models (VLM), multimodal systems, and image processing.

- A strong background in designing image understanding, multimodal, and cross-domain learning algorithms.

- Hands-on experience with deployable, Real-time Vision Language Models (VLMs).

- Practical experience with acceleration frameworks such as NVIDIA TensorRT, DeepStream, and Intel OpenVINO is preferred.

- Proficiency in programming languages including Python or C++.

- Experience with Docker and Kubernetes.

- Knowledge of pattern recognition and Edge AI product development.

- Ability to review code, design architectures, and document core components.

- Familiarity with research and development practices and industry standards.

- Preferred: Hands-on experience with Natural Language Processing (NLP) and the integration of visual and textual signals for multimodal systems.