AI/ML - Developer

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.
• Strong 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.