Artificial Intelligence Software Developer

We are seeking a seasoned software developer to spearhead the creation of innovative AI and machine learning solutions. As a key member of our team, you will be responsible for designing, developing, and deploying cutting-edge AI/ML technologies at an enterprise level.

The ideal candidate will possess hands-on experience in computer vision, deep learning, generative AI, and GIS-based AI applications. Strong programming skills in Python, along with expertise in TensorFlow, PyTorch, Keras, scikit-learn, NumPy, Pandas, and OpenCV, are essential. Proficiency in image classification using advanced CV models, such as ResNet, VGG, YOLOv5/v8, and EfficientNet, is also required.

A strong foundation in mathematics, statistics, data structures, algorithms, and optimization techniques is necessary for success in this role. Experience with RNNs/LSTMs, hybrid neural architectures, and temporal/spatiotemporal modeling is highly desirable. Additionally, familiarity with Agentic AI systems, including AI agents, multi-agent workflows, or autonomous agent design, is a plus.

GIS domain expertise, demonstrated ability to integrate AI/ML with geospatial datasets, satellite imagery, and spatial analytics to deliver practical solutions, is also expected. End-to-end experience in AI/ML solution lifecycle – from data preprocessing, model training, evaluation, deployment, and scaling – is crucial.

This role requires 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 is also necessary. Practical exposure to geospatial feature extraction, change detection, and segmentation workflows is highly desirable.

This position offers a unique opportunity to contribute to the development of AI-powered GIS platforms, multimodal and geospatially aware models, and real-time feature detection systems. If you are a skilled software developer with a passion for AI and machine learning, we encourage you to apply.

Required Skills:

• 3–5 years of hands-on experience in implementing AI/ML solutions in enterprise or large-scale production 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.

Bonus Skills:

• 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.