Skip to main content

Opens Honeywell's site. Your application data stays with them.Apply early.

LocationBengaluru, Karnataka, India
WorkplaceOn-site
ExperienceNot stated
CompensationUndisclosed

Job Overview

Responsibilities

*Key Responsibilities*

-

Design, develop, train, evaluate, and deploy machine learning and deep learning models.

-

Develop and optimize Generative AI applications using Large Language Models (GPT, Llama, Claude, Mistral, etc.).

-

Build Retrieval-Augmented Generation (RAG) solutions using vector databases.

-

Fine-tune foundation models and implement prompt engineering strategies.

-

Create scalable AI pipelines for data ingestion, feature engineering, model training, and inference.

-

Develop AI-powered applications, chatbots, recommendation engines, and predictive analytics solutions.

-

Implement MLOps practices including automated training, deployment, monitoring, and retraining.

-

Work with cross-functional teams to translate business requirements into AI solutions.

-

Optimize model performance, latency, accuracy, and cost efficiency.

-

Ensure AI governance, model explainability, privacy, and responsible AI practices.

-

Stay current with emerging AI technologies and recommend innovations.

Qualifications

*Required Skills & Qualifications*

Technical Skills

-

Machine Learning & AI

-

Generative AI

-

Strong understanding of: Supervised and Unsupervised Learning, Regression and Classification, Clustering, Recommendation Systems, Time-Series Forecasting, Reinforcement Learning, Deep Learning

-

Experience with: LLMs (GPT, Llama, Gemini, Claude, Mistral), RAG architectures, Prompt Engineering, Fine-tuning and PEFT techniques,  LangChain / LangGraph, Semantic Kernel, AI Agents and Multi-Agent Systems

-

Programming

-

Expert-level Python development

-

Strong knowledge of: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch

-

MLOps & Deployment: Docker, Kubernetes, MLflow, CI/CD pipelines, Model Monitoring, Azure ML / AWS SageMaker / Vertex AI

-

Data Technologies: SQL, Spark/PySpark, Data Engineering concepts, ETL pipelines, Feature Stores

-

Vector Databases: Pinecone, ChromaDB, Weaviate, Azure AI Search, FAISS

-

Cloud Platforms

-

Experience in at least one:

Microsoft Azure AI Services

Azure OpenAI

AWS AI/ML Services

Google Vertex AI

Posting Information

Posted4 Nov 2026
Expires25 Nov 2026
SourceCareer page - Honeywell

You apply at Honeywell. We don't take the CV.