Role Overview

RMSI is looking for an experienced AI/ML professional to lead the development of scalable AI solutions across sustainability, geospatial intelligence, climate risk, Earth observation, infrastructure, and enterprise analytics. The role combines hands-on technical leadership with AI strategy, team development, productization, and client engagement.

Key Responsibilities

- Define and execute the AI/ML strategy, technology roadmap, architecture, and governance framework.
- Lead multidisciplinary teams of AI/ML engineers, data scientists, geospatial specialists, data engineers, and MLOps professionals.
- Develop AI solutions using geospatial data, satellite imagery, weather and climate datasets, scientific models, and enterprise data.
- Drive the adoption of Generative AI, computer vision, multimodal AI, RAG, knowledge graphs, time-series models, and AI agents.
- Establish MLOps and LLMOps pipelines for model deployment, evaluation, monitoring, retraining, version control, and cost optimization.
- Convert research and prototypes into secure, explainable, scalable, and commercially viable AI products.
- Establish responsible AI standards covering model validation, explainability, bias, data privacy, security, and human oversight.
- Support solution design,



client engagements, proposals, partnerships, demonstrations, and AI-led business growth.
- Mentor technical teams and conduct architecture, model, and code reviews.

Required Profile

- Masters degree or PhD in AI, Computer Science, Data Science, Geoinformatics, Engineering, or a related discipline.
- 8-10 years of overall experience, including at least 4-6 years of hands-on AI/ML experience and demonstrated technical leadership.
- Robust knowledge of machine learning, deep learning, computer vision, NLP, Generative AI, and time-series modelling.
- Advanced proficiency in Python and frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face.
- Experience with LLMs, prompt engineering, embeddings, vector databases, RAG, and AI-agent frameworks.
- Experience with cloud platforms, data engineering, APIs, microservices, Docker, Kubernetes, and MLOps.

Preferred Experience

- GeoAI, GIS, satellite imagery, remote sensing, and spatial analytics.
- Sustainability, climate risk, natural resources, infrastructure, utilities, or telecommunications.
- Scientific machine learning, graph learning, digital twins, or high-performance computing.

📌 Senior Technical Specialist AI ML (Noida)
🏢 Rmsi
📍 Noida