Walk-in || AI/ML (Bengaluru)

Walk-In Drive | AI/ML Engineer (6-12 Years) | Bengaluru

Time : 9:30am - 1:30Pm

Date : 24th October 2026

Location: Bengaluru (venue details will be shared later)

Kindly carry the following documents:

• Updated Resume
• Government issued Photo ID - PAN card or Aadhaar card(Original & Copy)
• One Passport size Photograph

Looking for an experienced AI/ML Engineer with strong expertise in Machine Learning, Generative AI, and AWS cloud technologies. The candidate will be responsible for building, deploying, and optimizing scalable ML solutions, developing GenAI applications, and implementing MLOps best practices for enterprise use cases.

Key Responsibilities

• Design, train, deploy, and monitor ML models using AWS SageMaker.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, model training, and deployment.
• Develop predictive analytics solutions using Scikit-learn, TensorFlow, PyTorch, XGBoost, and LightGBM.
• Build GenAI solutions using GPT, Llama, Gemini, LangChain, LlamaIndex, AI Agents, and RAG frameworks.
• Implement MLOps practices including CI/CD, model versioning, monitoring, and automated deployments.
• Integrate AI/ML solutions with AWS services such as S3, Lambda, Glue, IAM, CloudWatch, and REST APIs.
• Collaborate with business and technical stakeholders to deliver scalable AI-driven solutions.

Required Skills

• Programming: Python, SQL
• ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM
• Generative AI: GPT APIs, LangChain, LlamaIndex, RAG, AI Agents, Prompt Engineering
• Cloud: AWS SageMaker, S3, Lambda, Glue, CloudWatch, IAM
• MLOps: SageMaker Pipelines, Model Registry, Docker, Jenkins, Git
• Data Engineering: Pandas, NumPy, Athena
• Strong understanding of model evaluation, feature engineering, and deployment best practices

Good to Have

• Geospatial Analytics (ArcGIS, GeoPandas, GDAL, OSMnx)
• Computer Vision and Multimodal AI
• Experience in enterprise automation, RFPs, and PoC development

Preferred Experience

• 5-8 years overall IT experience with 3+ years in AI/ML.
• Hands-on experience deploying production-grade AI/ML solutions on AWS.
• Experience building GenAI applications and AI-powered automation solutions.