Job highlights

- 5-8 years experience in AI/ML development with expertise in AWS SageMaker, Python, TensorFlow, PyTorch, and Geospatial AI
- Develop, deploy, and automate AI/ML models using AWS ecosystem and generative AI techniques for geospatial analytics

Role- AI/ML - Developer Desired Experience Range- 5-8 Yrs

Location- Pan India

Profile Summary

- 5 years of professional experience, including 4 years in AI/ML solution development and deployment across cloud and geospatial domains.
- Hands-on expertise in AWS SageMaker for model training, tuning, deployment (endpoints), and pipeline automation.
- Solid command over Python, Scikit-learn, TensorFlow, and PyTorch frameworks for building scalable ML pipelines.
- Proficient in XGBoost, LightGBM, and ensemble-based modeling techniques for predictive analytics.
- Experienced in data preprocessing, feature engineering, and ETL automation using Pandas, NumPy, and AWS Glue.
- Well-versed with the AWS ecosystem S3, Lambda, IAM, CloudWatch,



ECR ensuring end-to-end model lifecycle management.
- Strong understanding of model evaluation, MLOps best practices, and performance optimization.
- Exposure to Generative AI models (GPT-4o, LLaMA, Gemini LLMs) for text, image, and tabular data generation.
- Domain exposure in Geospatial AI, developing automation and analytics solutions for enterprise GIS environments.

Technical Skills

- Programming: Python, SQL
- AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM
- Generative AI: OpenAI GPT APIs, LangChain, LlamaIndex, Diffusion Models
- Cloud Platforms: AWS SageMaker, S3, Lambda, Glue, CloudWatch, IAM
- Data Tools: Pandas, NumPy, Matplotlib, AWS Athena
- Versioning / CI-CD: Git, Docker, Jenkins
- MLOps & Deployment: Sage Maker Pipelines, Model Registry, REST API Integration
- GIS Integration: ArcGIS, OSMnx, GDAL, Geo Pandas.

📌 AI/ML - Developer (Hyderabad)
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