AIML Engineer

As an AI/ML Engineer with 4-5 years of experience, your role will involve designing, developing, and deploying machine learning models and AI-driven solutions. Your expertise in data science, model building, and production deployment will be crucial in solving complex problems effectively. Key Responsibilities: - Design, develop, and optimize machine learning and deep learning models for real-world applications - Work with large datasets including data cleaning, preprocessing, and feature engineering - Build and deploy scalable ML pipelines in production environments - Collaborate with cross-functional teams such as product, data engineering, and software teams - Implement NLP, computer vision, or predictive analytics solutions based on business needs - Monitor model performance, retrain models as required, conduct A/B testing, and performance tuning - Stay updated with the latest advancements in AI/ML technologies Qualifications Required: - Bachelors or Masters degree in Computer Science, Data Science, or a related field - 4+ years of hands-on experience in AI/ML development - Strong programming skills in Python (mandatory) - Experience with ML libraries/frameworks like TensorFlow, PyTorch, Scikit-learn - Solid understanding of supervised & unsupervised learning, deep learning concepts, and model evaluation techniques - Experience with data handling tools such as Pandas, NumPy, SQL - Familiarity with cloud platforms like AWS, Azure, GCP - Experience in deploying models using APIs like Flask/FastAPI - Knowledge of version control using Git and CI/CD pipelines Preferred Qualifications: - Experience with NLP (e.g., Transformers, BERT) or Computer Vision - Exposure to MLOps tools like MLflow, Kubeflow, Docker, Kubernetes - Knowledge of big data tools such as Spark, Hadoop - Experience working in Agile/Scrum environments (Note: No additional company details were provided in the job description) As an AI/ML Engineer with 4-5 years of experience, your role will involve designing, developing, and deploying machine learning models and AI-driven solutions. Your expertise in data science, model building, and production deployment will be crucial in solving complex problems effectively. Key Responsibilities: - Design, develop, and optimize machine learning and deep learning models for real-world applications - Work with large datasets including data cleaning, preprocessing, and feature engineering - Build and deploy scalable ML pipelines in production environments - Collaborate with cross-functional teams such as product, data engineering, and software teams - Implement NLP, computer vision, or predictive analytics solutions based on business needs - Monitor model performance, retrain models as required, conduct A/B testing, and performance tuning - Stay updated with the latest advancements in AI/ML technologies Qualifications Required: - Bachelors or Masters degree in Computer Science, Data Science, or a related field - 4+ years of hands-on experience in AI/ML development - Strong programming skills in Python (mandatory) - Experience with ML libraries/frameworks like TensorFlow, PyTorch, Scikit-learn - Solid understanding of supervised & unsupervised learning, deep learning concepts, and model evaluation techniques - Experience with data handling tools such as Pandas, NumPy, SQL - Familiarity with cloud platforms like AWS, Azure, GCP - Experience in deploying models using APIs like Flask/FastAPI - Knowledge of version control using Git and CI/CD pipelines Preferred Qualifications: - Experience with NLP (e.g., Transformers, BERT) or Computer Vision - Exposure to MLOps tools like MLflow, Kubeflow, Docker, Kubernetes - Knowledge of big data tools such as Spark, Hadoop - Experience working in Agile/Scrum environments (Note: No additional company details were provided in the job description)