AI Engineer
2 weeks ago
About the Role
We are seeking an experienced AI Engineer with expertise in computer vision to join our team at Talent Pal. The ideal candidate will have a strong background in developing and deploying AI models for surveillance applications.
Key Responsibilities
- Algorithm Development: Design, develop and optimize computer vision algorithms and models for various surveillance applications, including object detection, tracking, activity recognition and anomaly detection.
- Data Analysis: Collect, preprocess and analyze large datasets to train and evaluate computer vision models, ensuring data quality and relevance for model accuracy.
- Model Training: Implement and fine-tune deep learning models using frameworks such as TensorFlow, PyTorch or Keras, applying techniques such as transfer learning and domain adaptation to enhance model performance.
- System Integration: Integrate AI models into real-time surveillance systems and ensure their seamless operation within existing infrastructure, collaborating with software engineers to deploy models effectively.
- Performance Optimization: Monitor and optimize the performance of computer vision systems, including processing speed, accuracy and resource utilization, identifying and resolving issues related to model performance.
- Research and Development: Stay up-to-date with the latest advancements in computer vision and AI, proposing and implementing innovative solutions to improve surveillance capabilities and address emerging challenges.
- Documentation and Reporting: Document model development processes, methodologies and results, preparing reports and presentations for internal and external stakeholders.
- Collaboration: Work closely with cross-functional teams, including data scientists, software engineers and project managers, to ensure successful project delivery.
Requirements
- Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Applied Mathematics or a related field, with advanced degrees being a plus.
- Experience: Proven experience in developing and deploying computer vision algorithms and models for surveillance or related applications, with demonstrated expertise in relevant tools and frameworks.
- Technical Skills:
- Proficiency in programming languages such as Python, C or Java.
- Strong knowledge of computer vision libraries and frameworks, including OpenCV, Dlib and TensorRT.
- Experience with deep learning frameworks, such as TensorFlow and PyTorch.
- Familiarity with cloud platforms, including AWS, Azure and Google Cloud, for deploying and scaling models.
- Analytical Skills: Strong problem-solving abilities and a solid understanding of machine learning principles and computer vision techniques.
- Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Team Player: Ability to work collaboratively in a fast-paced environment and contribute effectively to team objectives.
Preferred Qualifications:
- Experience with surveillance-specific applications, including facial recognition, license plate recognition or behavior analysis.
- Knowledge of data privacy and security considerations related to surveillance systems.
- Experience with edge computing and real-time processing constraints.
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