Job
Description
As an AI Engineer with 4+ years of experience in building and deploying AI/ML solutions, you will be responsible for the following key responsibilities: - Designing, developing, and deploying machine learning and deep learning models for various business use cases. - Building scalable, end-to-end AI pipelines including data preprocessing, model training, evaluation, and production deployment. - Collaborating with product, engineering, and data teams to translate business requirements into AI-driven solutions. - Optimizing models for performance, accuracy, and scalability in production environments. - Conducting research on emerging AI/ML techniques and evaluating their applicability to ongoing projects. - Monitoring deployed models, ensuring reliability, and implementing continuous improvements. Qualifications Required: - 4+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role. - Strong understanding of ML/DL algorithms, model development, and evaluation techniques. - Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn. - Hands-on experience in building and deploying models on cloud platforms (AWS, Azure, GCP). - Knowledge of data engineering concepts, including ETL pipelines and distributed computing. - Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow, etc.) is a strong plus. - Solid grasp of software engineering principles, version control, and CI/CD practices. - Strong problem-solving skills and the ability to work independently in a fast-paced environment. Please note that this information is based on the job description provided by the company. As an AI Engineer with 4+ years of experience in building and deploying AI/ML solutions, you will be responsible for the following key responsibilities: - Designing, developing, and deploying machine learning and deep learning models for various business use cases. - Building scalable, end-to-end AI pipelines including data preprocessing, model training, evaluation, and production deployment. - Collaborating with product, engineering, and data teams to translate business requirements into AI-driven solutions. - Optimizing models for performance, accuracy, and scalability in production environments. - Conducting research on emerging AI/ML techniques and evaluating their applicability to ongoing projects. - Monitoring deployed models, ensuring reliability, and implementing continuous improvements. Qualifications Required: - 4+ years of experience as an AI Engineer, Machine Learning Engineer, or similar role. - Strong understanding of ML/DL algorithms, model development, and evaluation techniques. - Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Keras, or Scikit-learn. - Hands-on experience in building and deploying models on cloud platforms (AWS, Azure, GCP). - Knowledge of data engineering concepts, including ETL pipelines and distributed computing. - Experience with MLOps tools (Docker, Kubernetes, MLflow, Airflow, etc.) is a strong plus. - Solid grasp of software engineering principles, version control, and CI/CD practices. - Strong problem-solving skills and the ability to work independently in a fast-paced environment. Please note that this information is based on the job description provided by the company.
