Artificial Intelligence

As a skilled AI/Machine Learning Engineer, you will be responsible for designing, developing, and deploying artificial intelligence solutions that drive business growth.

Key Responsibilities:

• Develop and implement machine learning algorithms to analyze complex data sets
• Design and develop computer vision systems for image classification and object detection
• Work with large datasets to build predictive models and improve existing ones
• Collaborate with cross-functional teams to integrate AI/ML solutions into enterprise applications
• Stay up-to-date with the latest advancements in AI/ML research and development

Requirements:

• 3-5 years of hands-on experience in implementing AI/ML solutions in enterprise environments
• Strong programming proficiency in Python with practical use of TensorFlow, PyTorch, Keras, scikit-learn, NumPy, Pandas, and OpenCV
• Proven experience with Computer Vision architectures, including YOLO, SAM, U-Net, and other CNN-based models 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 and implementation experience 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
• 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

Preferred Qualifications:

• Working knowledge of 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
• Practical exposure to geospatial feature extraction, change detection, and segmentation workflows
• Strong ability to communicate AI/GIS solutions, collaborate with cross-functional teams, and translate research into applied enterprise use cases

Nice to Have:

• Certifications in AI/ML, GIS, or cloud platforms (AWS, Azure, GCP)
• Familiarity with scientific computing libraries (SciPy, Theano, Julia ecosystem)
• Experience contributing to AI/GIS research publications, open-source projects, or innovation programs
• Knowledge of emerging paradigms such as federated learning, multi-agent systems, spatial AI, or Responsible AI practices

Why Join Our Team?

We are looking for talented AI/Machine Learning Engineers who are passionate about driving business growth through innovative AI solutions. If you have a strong background in AI/ML and a passion for delivering high-quality results, we would love to hear from you

What We Offer:

We offer a dynamic and collaborative work environment, opportunities for professional growth and development, and a competitive compensation package.