Artificial Intelligence Model Specialist

2 days ago

Pune, Maharashtra, India beBeeMachineLearning Full time

Are you a skilled Machine Learning Engineer looking for a challenging role that leverages your expertise in Python and TensorFlow? This position offers the perfect opportunity to develop, optimize, and deploy sophisticated ML and Deep Learning models in a fast-paced environment.

Key Responsibilities
  • Data Analysis & Feature Engineering: Conduct comprehensive feature engineering, data analysis, and data exploration to extract valuable insights from diverse datasets. You will work with complex data sets to identify patterns, trends, and correlations that inform business decisions.
  • Model Development & Optimization: Develop and optimize cutting-edge Machine Learning models to achieve high accuracy, efficiency, and performance. Your expertise in model evaluation and selection will enable you to choose the best approach for each problem.
  • Deep Learning Implementation: Design and implement advanced Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. Your ability to select the right algorithm and configure it effectively will be critical to success.
  • Imbalanced Data Handling: Effectively handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness, generalization, and robustness. Your experience with class imbalance and over/under sampling will be invaluable.
  • Model Deployment & Monitoring: Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on real-world feedback and performance metrics. Your attention to detail and analytical skills will help identify areas for improvement.
  • Cross-Functional Collaboration: Collaborate seamlessly with cross-functional teams, including data scientists, software engineers, and product managers, to align ML solutions with overarching business goals. Your excellent communication and interpersonal skills will facilitate effective collaboration.
  • Statistical & Mathematical Application: Utilize fundamental statistical knowledge and strong mathematical principles to ensure the reliability, validity, and interpretability of models. Your expertise in probability, statistics, and linear algebra will be essential to modeling and decision-making.
Requirements
  • Hands-on experience in Machine Learning and Deep Learning.
  • Strong expertise in feature engineering, data exploration, and data preprocessing.
  • Experience with imbalanced datasets and techniques to improve model generalization.
  • Proficiency in Python, TensorFlow, Scikit-learn, and other relevant ML frameworks and libraries.
  • Strong mathematical and statistical knowledge coupled with excellent problem-solving skills.
  • Ability to optimize models for high accuracy and performance in real-world scenarios.
Preferred Qualifications
  • Experience with Big Data technologies (e.g., Hadoop, Spark).
  • Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
  • Experience in automating ML pipelines with MLOps practices.
  • Experience in model deployment using cloud platforms (e.g., AWS, GCP, Azure) or MLOps tools.

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