Chief Artificial Intelligence Engineer

2 weeks ago

Bharatpur, Rajasthan, India beBeeSoftwareDeveloper Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Description:

Our organization seeks a highly skilled AI/ML Software Developer to design, develop, and deploy cutting-edge AI and machine learning solutions at an enterprise level.

The ideal candidate will have extensive experience in computer vision, deep learning, generative AI, and GIS-based AI applications, along with strong programming, analytical, and problem-solving skills.

  • Design, develop, and deploy AI/ML solutions in large-scale production environments.
  • Implement AI/ML models using Python with TensorFlow, PyTorch, Keras, scikit-learn, NumPy, Pandas, and OpenCV.
  • Develop and implement computer vision architectures for real-time object detection, segmentation, and feature extraction.
  • Expertise in image classification using advanced CV models (e.g., ResNet, VGG, YOLOv5/v8, EfficientNet).
  • Deep understanding of machine learning algorithms (supervised, unsupervised, and reinforcement learning) for classification, regression, and clustering.
  • Experience in Generative AI and Large Language Models (LLMs), including transformers, diffusion models, multimodal pipelines, and speech-to-text/NLP solutions.
Required Skills and Qualifications:
  • Strong foundation in mathematics, statistics, data structures, algorithms, and optimization techniques.
  • Hands-on experience with RNNs/LSTMs, hybrid neural architectures, and temporal/spatiotemporal modeling.
  • Practical knowledge of agentic AI systems (AI agents, multi-agent workflows, or autonomous agent design).
  • GIS domain expertise – demonstrated ability to integrate AI/ML with geospatial datasets, satellite imagery, and spatial analytics to deliver practical solutions.
  • End-to-end experience in AI/ML solution lifecycle – from data preprocessing, model training, evaluation, deployment, and scaling.
Benefits:
  • MLOps/LLMOps workflows for scalable, automated AI/ML deployments (CI/CD, containerization, orchestration).
  • Experience with enterprise-grade data platforms (cloud-native, distributed systems) ensuring high performance and interoperability with AI workloads.
  • Familiarity with scientific computing libraries (SciPy, Theano, Julia ecosystem).

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