Machine Learning & Generative AI Specialist
Recro
All India • 2 months ago
Experience: 4 to 8 Yrs
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Job Description
As an AI Engineer with 4+ years of experience in Bangalore, your role will involve:
- Data visualization to drive insights in the energy sector
- Implementing data science solutions using machine learning, NLP, Gen AI, and deep learning techniques to optimize business outcomes
- Evaluating the quality and effectiveness of data sources and data collection methodologies
- Translating complex technical concepts into clear, actionable insights
Your technical expertise should include proficiency in the following areas:
- Cloud Platforms: Designing, developing, and deploying data science solutions on Azure, specifically Azure Machine Learning, Azure Databricks, and Azure Storage
- Programming Languages: Proficiency in Python for data manipulation and analysis using Pandas and NumPy, as well as machine learning and deep learning using scikit-learn, TensorFlow, and PyTorch
- Machine Learning: Developing and deploying machine learning models for supervised and unsupervised learning, regression, classification, and clustering, as well as model evaluation and selection
- Optimizer: Using optimization techniques such as linear and nonlinear programming, and stochastic optimization to improve asset performance
- Deep Learning Models: Developing and deploying models like Convolutional neural networks (CNNs), Recurrent neural networks (RNNs), and Long short-term memory (LSTM) networks
- Generative AI: Exploring and applying generative AI techniques like Generative adversarial networks (GANs) and Variational autoencoders (VAEs), as well as Transformers
To be eligible for this role, you should have:
- A Bachelors degree in computer science, Data Science, Statistics, Mathematics, or a related field; a masters degree is preferred
- 46 years of hands-on experience in data science or a related role, with a proven track record of successful project delivery As an AI Engineer with 4+ years of experience in Bangalore, your role will involve:
- Data visualization to drive insights in the energy sector
- Implementing data science solutions using machine learning, NLP, Gen AI, and deep learning techniques to optimize business outcomes
- Evaluating the quality and effectiveness of data sources and data collection methodologies
- Translating complex technical concepts into clear, actionable insights
Your technical expertise should include proficiency in the following areas:
- Cloud Platforms: Designing, developing, and deploying data science solutions on Azure, specifically Azure Machine Learning, Azure Databricks, and Azure Storage
- Programming Languages: Proficiency in Python for data manipulation and analysis using Pandas and NumPy, as well as machine learning and deep learning using scikit-learn, TensorFlow, and PyTorch
- Machine Learning: Developing and deploying machine learning models for supervised and unsupervised learning, regression, classification, and clustering, as well as model evaluation and selection
- Optimizer: Using optimization techniques such as linear and nonlinear programming, and stochastic optimization to improve asset performance
- Deep Learning Models: Developing and deploying models like Convolutional neural networks (CNNs), Recurrent neural networks (RNNs), and Long short-term memory (LSTM) networks
- Generative AI: Exploring and applying generative AI techniques like Generative adversarial networks (GANs) and Variational autoencoders (VAEs), as well as Transformers
To be eligible for this role, you should have:
- A Bachelors degree in computer science, Data Science, Statistics, Mathematics, or a related field; a masters degree is preferred
- 46 years of hands-on experience in data science or a related role, with a proven track record of successful project delivery
Skills Required
Data visualization
Machine learning
NLP
Deep learning
Python
NumPy
Unsupervised learning
Regression
Classification
Clustering
Linear programming
Stochastic optimization
Transformers
Azure Machine Learning
Azure Databricks
Azure Storage
Pandas
scikitlearn
TensorFlow
PyTorch
Supervised learning
Model evaluation
Nonlinear programming
Convolutional neural networks CNNs
Recurrent neural networks RNNs
Long shortterm memory LSTM networks
Generative adversarial networks GANs
Variational autoencoders VAEs
Posted on: March 5, 2026
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