Ai Ml Engineer

Manpowergroup Services India; Bengaluru; Sur place; INR 900 000 - 1 500 000; Plein temps

Résumé du poste

Manpowergroup Services India invites applications for an AI/ML Engineer / Data Scientist in Bengaluru. The role focuses on developing and implementing machine learning models, forecasting solutions, predictive analytics, and AI-driven applications using real-world datasets.

You will explore Generative AI and LLM applications, build dashboards, and integrate models with software and REST APIs while collaborating with data teams and domain experts to deliver scalable AI solutions.

Qualifications

• Proficiency in Python and ML libraries such as Pandas, NumPy, and Scikit-learn.
• Strong knowledge of ML fundamentals: regression, classification, clustering, evaluation metrics.
• Experience with time-series forecasting techniques and model evaluation.

Responsabilités

• Develop, train, validate, and maintain ML models for forecasting, prediction, classification, and anomaly detection.
• Data cleaning, preprocessing, EDA, and feature engineering.
• Build time-series forecasting models using historical and real-time data.
• Apply statistical analysis and hypothesis testing to derive insights.
• Evaluate models using MAE, RMSE, and MAPE metrics.
• Work with Generative AI, LLMs, embeddings, and RAG applications.
• Develop visualizations, dashboards, and reports to communicate findings.
• Integrate AI/ML models with software apps and REST APIs.
• Support deployment, monitoring, and continuous improvement.
• Collaborate with engineers, data teams, and domain experts to translate business needs into AI/ML solutions.

Connaissances

Python

Pandas

NumPy

Scikit-learn

Matplotlib

SQL

Time-series forecasting

ML concepts

Description du poste

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.