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Manpowergroup Services India

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Ai Ml Engineer

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Summary

Junior AI/ML Engineer / Data Scientist (1-3 yrs) in Bengaluru building machine learning, time-series forecasting, and predictive analytics models for the renewable energy sector (solar, wind, BESS), plus Generative AI/LLM apps with RAG. Core stack: Python, Pandas, NumPy, Scikit-learn, SQL.

Job Title: AI/ML Engineer / Data Scientist


Location: Bangalore
Experience: 1 to 3 Years
Industry: Renewable Energy | Solar | Wind | BESS | Grid Automation


Job Summary


Seeking an AI/ML Engineer / Data Scientist to develop and implement machine learning models, forecasting solutions, predictive analytics, and AI-driven applications. The role involves working with real-world datasets to build predictive models, derive business insights, improve model performance, and explore Generative AI and Large Language Model (LLM) applications.


Key Responsibilities


  • Develop, train, validate, and maintain machine learning models for forecasting, prediction, classification, and anomaly detection.
  • Perform data cleaning, preprocessing, exploratory data analysis (EDA), and feature engineering.
  • Build time-series forecasting models using historical and real-time data.
  • Apply statistical analysis, hypothesis testing, and experimentation to derive actionable business insights.
  • Evaluate and optimize models using appropriate performance metrics such as MAE, RMSE, and MAPE.
  • Work with Generative AI, LLMs, prompt engineering, embeddings, and Retrieval-Augmented Generation (RAG) applications.
  • Develop data visualizations, dashboards, and analytical reports to communicate findings effectively.
  • Integrate AI/ML models with software applications and REST APIs.
  • Support model deployment, performance monitoring, documentation, and continuous improvement.
  • Collaborate with software engineers, data teams, and domain experts to translate business requirements into AI/ML solutions.

Required Skills


  • Strong programming skills in Python.
  • Hands-on experience with Pandas, NumPy, Scikit-learn, and data visualization libraries such as Matplotlib.
  • Good knowledge of SQL and databases.
  • Strong understanding of machine learning, statistics, probability, regression, classification, clustering, and model evaluation.
  • Knowledge of time-series forecasting techniques such as ARIMA/SARIMA, Exponential Smoothing, Prophet, and ML-based forecasting.

Preferred Skills


  • Exposure to TensorFlow, PyTorch, XGBoost, or LightGBM.
  • Familiarity with LangChain, OpenAI, Azure OpenAI, Gemini, Claude, embeddings, vector databases, and RAG.
  • Knowledge of AI agents, tool calling, and workflow automation.
  • Exposure to FastAPI, Git, Docker, Linux, cloud platforms, and CI/CD.
  • Experience or project exposure in renewable energy, power systems, industrial IoT, forecasting, or optimization.


Skills

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