3 Hyperparameter Optimization Jobs

The role of a member in the New Analytics Team based in Hyderabad involves understanding business processes and data to model requirements for creating analytics solutions. You will be responsible for building predictive models and recommendation engines using cutting-edge machine learning techniques to enhance the efficiency and effectiveness of business processes. Your tasks will include churning and analyzing data to identify actionable insights and patterns for business use. Additionally, you will assist the Function Head in data preparation and modeling tasks as required. Collaboration with both business and IT teams is essential for understanding and collecting data. Your responsibilities will also include collecting, collating, cleaning, processing, and transforming large volumes of primarily tabular data comprising numerical, categorical, and some textual information. Applying data preparation techniques such as data filtering, joining, cleaning, missing value imputation, feature extraction, feature engineering, feature selection, dimensionality reduction, feature scaling, and variable transformation will be a part of your routine tasks. You will be expected to apply basic algorithms like linear regression, logistic regression, ANOVA, KNN, various clustering methods, SVM, Naive Bayes, decision trees, principal components, and association rule mining. Additionally, ensemble modeling algorithms like bagging (Random Forest), boosting (GBM, LGBM, XGBoost, CatBoost), time-series modeling, and other state-of-the-art algorithms will also be utilized as required. Your role will involve employing modeling concepts such as hyperparameter optimization, feature selection, stacking, blending, K-fold cross-validation, bias and variance, and combating overfitting. Building predictive models using state-of-the-art machine learning techniques for regression, classification, clustering, recommendation engines, etc., will be a key part of your responsibilities. Furthermore, you will analyze business data to uncover hidden patterns and insights, identify explanatory causes, and make strategic recommendations based on your findings. To excel in this role, you should hold a BE/B. Tech degree in any stream and possess strong expertise in Python libraries like Pandas and Scikit Learn. Proficiency in coding according to the outlined requirements is essential. Experience with Python editors such as PyCharm and/or Jupyter Notebooks is a must, along with the ability to organize code into modules, functions, and/or objects. Knowledge of using ChatGPT for machine learning will be advantageous, while familiarity with basic SQL for querying and Excel for data analysis is necessary. Understanding basics of statistics, including distributions, hypothesis testing, and sampling techniques, is a prerequisite. Experience with Kaggle and familiarity with R are desirable. Ideal candidates will have a minimum of 4 years of experience solving business problems through data analytics, data science, and modeling, with at least 2 years of full-time experience as a data scientist. They should have worked on at least 3 projects involving ML model building that were utilized in production by businesses or other clients. Your primary responsibilities will include spending 35% of your time on data preparation for modeling, 35% on building ML/AI models for various business requirements, 20% on performing custom analytics to provide actionable insights to the business, and 10% on assisting the Function Head in data preparation and modeling tasks as needed. Candidates without familiarity with deep learning algorithms, image processing and classification, and text modeling using NLP techniques will not be considered for selection. For applying to this position, please email your application to careers@isb.edu.,

You will be joining a Pune-based startup as an AI Research Specialist. Your primary responsibility will involve conducting thorough research on emerging AI models, analyzing their potential integration with our system, and providing expert advice on optimizing model performance. Key Responsibilities: - Monitoring and analyzing new AI models entering the market. - Assessing the applicability of emerging models to our AI agent system. - Providing insights on model architectures, weights, biases, and training methods. - Developing and recommending fine-tuning strategies for optimal performance. - Optimizing model efficiency by determining the minimal necessary layer structure. Required Qualifications: - Holding an advanced degree in Computer Science (MS or PhD), Machine Learning, Engineering, Applied Mathematics, or related quantitative field. Candidates with backgrounds in Control Theory, Information Theory, or similar disciplines are particularly encouraged to apply. - Possessing extensive knowledge of various AI model architectures and their inner workings. - Demonstrating a strong understanding of neural network fundamentals, including weights, biases, and activation functions. - Having experience with model fine-tuning and hyperparameter optimization. - Proficiency in Python and common ML frameworks (e.g., TensorFlow, PyTorch). - Being familiar with state-of-the-art AI research and having the ability to quickly grasp new concepts. - Demonstrating the ability to apply systematic, logical thinking to complex problems, particularly in model optimization and efficiency. - Possessing excellent analytical and problem-solving skills. - Strong communication skills to convey complex technical concepts clearly. Preferred Skills: - Knowledge of Control Theory concepts (e.g., feedback systems, stability analysis). - Familiarity with Information Theory principles.,

You will be joining a Pune based startup as an AI Research Specialist. Your primary responsibility will involve conducting thorough research on emerging AI models, analyzing their potential integration with our system, and providing expert advice on optimizing model performance. Your key responsibilities will include monitoring and analyzing new AI models entering the market, assessing the applicability of emerging models to our AI agent system, providing insights on model architectures, weights, biases, and training methods, developing and recommending fine-tuning strategies for optimal performance, and optimizing model efficiency by determining the minimal necessary layer structure. To qualify for this role, you should have an advanced degree in Computer Science (MS or PhD), Machine Learning, Engineering, Applied Mathematics, or related quantitative field. Candidates with backgrounds in Control Theory, Information Theory, or similar disciplines are particularly encouraged to apply. You are expected to have extensive knowledge of various AI model architectures and their inner workings, a strong understanding of neural network fundamentals including weights, biases, and activation functions, experience with model fine-tuning and hyperparameter optimization, proficiency in Python and common ML frameworks such as TensorFlow and PyTorch, familiarity with state-of-the-art AI research, and the ability to quickly grasp new concepts. Additionally, you should demonstrate a systematic, logical approach to complex problems, particularly in model optimization and efficiency, possess excellent analytical and problem-solving skills, and have strong communication abilities to convey complex technical concepts clearly. Preferred skills include knowledge of Control Theory concepts such as feedback systems and stability analysis, as well as familiarity with Information Theory principles.,