Artificial Intelligence

Key Accountabilities:

• Lead the design and enhancement of ML and DL algorithms to elevate our product suite.
• Strategize with cross-functional teams to unearth and tackle intricate challenges using AI, computer vision, sensor fusion, and advanced predictive models.
• Pioneer the architecture and deployment of cutting-edge CV algorithms and ML models tailored for intricate video analytics.
• Orchestrate advanced predictive models utilizing the latest machine learning algorithms and comprehensive data scrutiny.
• Analyze multifaceted datasets, drawing out critical insights for business needs.
• Design sophisticated data visualizations to lucidly present findings to stakeholders.
• Steer the development and calibration of models for sensor fusion discrepancies.
• Pilot the deployment of predictive models in real-world scenarios, shaping pivotal business strategies.
• Interpret diverse video inputs from sources like cameras, sensors, and drones, filtering out the essence.
• Push the envelope in deep learning applications, exploring realms like CNN, RNN, LSTM, and GANs for astute video dissection.
• Forge ahead in object detection, tracking, and recognition arenas.
• Persistently assess the efficacy of models, algorithms, and fusion techniques, advocating evolutionary shifts.
• Engage in contemporary research, staying abreast with the forefront of AI, computer vision, and predictive analytics.
• Comprehensively document discoveries and engage in dialogues with both internal teams and external peers.
  

Experience & Education Qualifications:

• A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or akin disciplines.
• A minimum of 2 years of hands-on experience in sculpting and deploying ML, CV, sensor fusion, and deep learning constructs.
• Adeptness and experienced in programming with Python, C++, or Matlab, and fluency with deep learning frameworks like TensorFlow, Keras, or PyTorch.
• Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
• Proficiency in optimization techniques, both for model training and real-time performance.
• Ability to design, conduct, and analyze A/B tests and other experimentation methodologies.
• Familiarity with advanced ML platforms and tools like NVIDIA DeepStream, MLflow, or Kubeflow.
• Deep understanding of edge computing and experience deploying AI/ML solutions on edge devices.
• Knowledge of cybersecurity best practices, especially related to AI and data protection.
• An analytical mind coupled with impeccable problem-solving prowess, adaptable to a dynamic work rhythm.
• Stellar communication faculties with a penchant for teamwork and collaboration.
• Demonstrable experience in materializing predictive models into tangible business applications.