Artificial Intelligence and Data Science Professional

4 days ago

hubballi, India beBeeMachineLearning Full time

Job Title: Data Science EngineerAt our company, we are seeking a highly skilled and experienced Data Science Engineer to lead the development of artificial intelligence systems. The ideal candidate should have strong expertise in machine learning, data science, and software development.Key Responsibilities:Develop and deploy efficient machine learning models for various applications.Collaborate with cross-functional teams to design and implement data-driven features.Optimize and improve the performance of existing machine learning models.Design and maintain scalable machine learning pipelines and infrastructure.Analyze and preprocess large datasets to extract valuable insights and features.Stay updated with the latest developments in machine learning, deep learning, and related technologies.Conduct model training, validation, and performance evaluation to ensure models meet the required accuracy and reliability.Document and communicate complex technical concepts effectively.Develop A/B testing frameworks and manage the deployment of models in production.Requirements:Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.3+ years of experience in AI and machine learning.Strong programming skills in Python, R, or similar languages.Proficiency with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, etc.Experience with data preprocessing, data wrangling, and data visualization.Hands-on experience with SQL databases and API integration.Experience with cloud platforms (AWS, GCP, or Azure) and deploying models in production.Solid understanding of machine learning algorithms, deep learning architectures, and statistical methods.Ability to work in a collaborative environment and communicate effectively with cross-functional teams.Nice-to-Have:Knowledge of natural language processing (NLP) and its applications.Experience with MLOps tools and best practices for scalable model deployment and monitoring.Familiarity with data privacy and security regulations.Experience with real-time data processing and streaming technologies.Experience with reinforcement learning, generative models, or unsupervised learning techniques.

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