Senior AI/ML Engineer

Position: Senior AI/ML Engineer (68Years) – GeoAI & Conversational Systems

Location:Hyderabad
Team: GeoAI & Intelligent Assistants

About the Role
We’re seeking a seasoned AI/ML expert with 6–8years of handson experience—particularly in geospatial intelligence (GeoAI) and conversational AI—to own the endtoend design, development, and deployment of advanced machinelearning solutions, including chatbots and “copilot” assistants. You will collaborate with GIS engineers, data scientists, and product teams to build systems that understand spatial data, power decisionsupport interfaces, and engage users via natural language.

Key Responsibilities
GeoAI Model Development:

Architect and train spatialanalysis models (e.g., landuse classification, object detection in satellite/drone imagery, changedetection pipelines)

Integrate geospatial features into ML workflows (e.g., spatial joins, coordinatebased embeddings, topological data structures)

Conversational AI & Copilot Systems:

Design, finetune, and deploy large language models (LLMs) for domainspecific chatbots and copilots

Implement NLU/NLG pipelines (intent/entity extraction, dialogue management, context handling)

Build guidance interfaces (“copilots”) that assist users—e.g., query GIS datasets, autogenerate map legends, suggest spatial analysis steps

Productionization & MLOps:

Containerize ML services (Docker/Kubernetes), set up CI/CD for model training and serving

Monitor model performance in production, implement A/B testing and continuous learning loops

Data Engineering & Integration:

Build and maintain ETL pipelines for largescale spatial and tabular datasets

Optimize geospatial databases (PostGIS, GeoMesa) and timeseries stores for ML feature retrieval

Collaboration & Leadership:

Mentor junior ML engineers and data scientists on best practices in GeoAI and NLP

Partner with product managers to translate requirements into technical specifications and roadmaps

Conduct code reviews, design reviews, and knowledgesharing sessions

Required Qualifications
Experience: 6–8years in applied AI/ML roles, with at least 2years focused on geospatial machine learning and 2years on NLP/Conversational AI

Technical Skills:

Proficient in Python and ML frameworks (TensorFlow, PyTorch, ScikitLearn)

GeoAI libraries: Rasterio, GDAL, GeoPandas, PyProj, or similar

NLP/LLM toolkits: Hugging Face Transformers, Rasa, Dialogflow, or equivalents

Experience finetuning and deploying LLMs (GPTseries, LLaMA, etc.) and integrating with vector databases (Pinecone, Qdrant)

Strong data engineering skills: SQL, PostGIS, Apache Spark or Dask for largescale processing

DevOps & MLOps:

Containerization (Docker), orchestration (Kubernetes), and CI/CD tooling (Jenkins, GitHub Actions)

Monitoring/logging (Prometheus, ELK/EFK stacks) and A/B testing frameworks

Problemsolving & Ownership:

Demonstrated ability to own features endtoend, from design through production

Strong analytical mindset, with experience troubleshooting model drift, performance degradation, and bias

Communication & Leadership:

Excellent verbal and written communication in English

Proven mentorship of junior engineers and ability to lead crossfunctional technical discussions

Preferred (NicetoHave)
Experience with realtime spatial analytics (e.g., streaming telemetry from IoT devices, geofencing alerts)

Familiarity with cloudnative geospatial platforms (AWSGround Station, Google Earth Engine, Azure Maps)

Background in userexperience design for chatbots or voice assistants (e.g., conversational UX best practices)

Publications or opensource contributions in GeoAI or NLP