Job Summary

We are looking for a highly skilled and hands-on Senior AI/ML & Generative AI Developer with strong experience in Machine Learning, Deep Learning, Time Series Forecasting, Generative AI, Large Language Models (LLMs), RAG, and production AI deployment.

The ideal candidate will work on developing and maintaining AI systems across renewable energy forecasting, predictive analytics, document intelligence, enterprise automation, and Generative AI applications. The role requires strong programming expertise in Python and R, hands-on experience with production-grade AI/ML systems, and the ability to design, deploy, monitor, and continuously improve AI solutions.

The candidate should also have exposure to LLM-based applications, Retrieval-Augmented Generation (RAG), Agentic AI/Multi-Agent workflows, cloud platforms, containerization, APIs, and CI/CD pipelines.

Key Roles & Responsibilities

AI/ML Model Development & Forecasting

- Develop, test, deploy, and maintain Machine Learning, Deep Learning, and Generative AI models.
- Build and maintain forecasting models for demand, wind, solar, renewable generation, and price forecasting.
- Work on intra-day and day-ahead forecasting models and continuously improve model accuracy.
- Perform feature engineering using weather, holiday, calendar, temporal, and historical signals.
- Conduct detailed error analysis for demand, wind, solar, and other forecasting models and implement improvements.
- Perform manual computations and validation for forecasting models when required.
- Apply statistical analysis, regression, clustering, predictive modelling, and advanced Machine Learning techniques.
- Perform data mining using state-of-the-art methods to identify patterns, insights, and predictive opportunities.
- Process, cleanse, validate, and verify the integrity and quality of datasets used for model training and analysis.
- Conduct in-depth analysis to solve complex business and domain-specific problems.

Generative AI & LLM Development

- Design and develop Generative AI applications for scenario generation, predictive modeling, enterprise automation, and domain-specific use cases.
- Build applications using Large Language Models (LLMs) and open-source AI models.
- Design and implement advanced Retrieval-Augmented Generation (RAG) solutions.
- Work with vector databases, semantic search, hybrid/fusion retrieval, reranking, and context compression.
- Develop and implement frameworks for RAG evaluation and hallucination detection.
- Work with LLM orchestration frameworks such as LangChain and/or LangGraph.




- Evaluate and select appropriate proprietary, open-source, and on-premises AI/LLM models based on performance, security, cost, latency, and business requirements.
- Develop agentic AI and Multi-Agent workflows for extraction, validation, reasoning, automation, and controlled code execution.
- Work with structured and unstructured datasets for AI and GenAI applications.
- Collaborate with cross-functional teams to integrate GenAI solutions into business and forecasting workflows.

Production AI Engineering & Deployment

- Deploy AI/ML and GenAI models as scalable and reliable production services.
- Develop APIs and AI services using FastAPI and/or Flask.
- Containerize applications and models using Docker.
- Deploy and manage AI applications on AWS and/or Azure.
- Work with orchestration, CI/CD pipelines, automated deployment, and production release processes.
- Monitor model performance, accuracy, availability, latency, and operational health.
- Design and manage automated or periodic model retraining workflows.
- Ensure production AI systems meet required standards for reliability, scalability, maintainability, and performance.
- Troubleshoot production issues and continuously optimise AI models and applications.

Automation & Programming

- Develop and optimise scripts using Python and R to automate data processing, forecasting, analysis, and operational workflows.
- Build reusable, scalable, and well-documented AI/ML pipelines.
- Improve existing systems through automation and process optimisation.
- Follow coding standards, version control, documentation, and software engineering best practices.

Team Collaboration & Technical Leadership

- Provide technical guidance and mentorship to junior AI/ML engineers.
- Participate in and conduct code reviews to maintain engineering quality and standards.
- Provide technical direction and contribute to architecture and technology decisions.
- Work closely with business stakeholders and cross-functional teams to understand requirements.
- Translate business problems into scalable and technically feasible AI/ML and GenAI solutions.
- Take ownership of self-assigned tasks and provide regular project and status updates.
- Collaborate with engineering, data,



product, and business teams throughout the development lifecycle.

Required Technical Skills

Programming & Data

- Strong hands-on experience in Python
- Working knowledge of R Programming
- Statistics and statistical modelling
- Data mining and data analysis
- Data preprocessing, cleansing, validation, and feature engineering
- Regression and clustering techniques

Machine Learning & Forecasting

- Machine Learning
- Deep Learning
- Predictive Analytics
- Time Series Forecasting
- Forecast model evaluation and error analysis
- Demand, wind, solar, renewable generation, or price forecasting experience preferred

Generative AI & LLMs

- Generative AI (GenAI)
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- LangChain and/or LangGraph
- Vector Databases
- Semantic Search
- RAG Evaluation
- Hallucination Detection
- Reranking
- Hybrid/Fusion Retrieval
- Agentic AI / Multi-Agent Systems

Production & Cloud

- FastAPI and/or Flask
- Docker / Containerisation
- AWS and/or Azure
- REST APIs
- CI/CD
- Production AI/ML Deployment
- Model Monitoring
- Model Retraining and Lifecycle Management

Preferred / Valuable to Have Skills

- Experience in the Renewable Energy, Energy, Utilities, or Power Forecasting domain
- Experience in Document Intelligence and Enterprise Automation
- Computer Vision
- Optical Character Recognition (OCR)
- Document Extraction
- Experience with open-source and on-premises AI/LLM models
- Experience with secure or air-gapped model deployment environments
- Power BI or other reporting and data visualisation tools
- Experience mentoring or leading technical teams
- Knowledge of software architecture and scalable AI system design

Candidate Profile

- 4-6 years of experience in applied machine learning, artificial intelligence, data science, or related areas.
- Demonstrated experience developing AI/ML models that have been deployed and used in production environments.
- Strong hands-on experience in Python and working knowledge of R.
- Experience in building machine learning and deep learning models.
- Hands-on experience with generative AI, LLMs, and RAG-based applications.
- Strong understanding of data processing, feature engineering, model evaluation, and error analysis.
- Experience with cloud deployment and containerization.
- Ability to solve complex technical and business problems independently.
- Strong communication and stakeholder management skills.
- Experience mentoring engineers or providing technical leadership will be preferred.

📌 Urgent Hiring: Associate/Sr. Associate- Artificial Intelligence (Ghaziabad)
🏢 Kreate Energy
📍 Ghaziabad