AI/ML Engineer

Corning Technologies is looking for AI/ML Engineer to join our dynamic team and embark on a rewarding career journey.

you will play a critical role in designing, developing, and deploying artificial intelligence and machine learning solutions that drive innovation and improve business outcomes. You will work closely with cross-functional teams to understand business needs, develop machine learning models, and create scalable, data-driven applications. Your expertise in AI/ML will enable us to harness the power of data for strategic advantage. Key Responsibilities : Solution Design : Collaborate with stakeholders to define AI/ML project requirements and objectives. Data Collection : Identify and gather relevant data from various sources, ensuring data quality and reliability. Data Preprocessing : Clean, preprocess, and transform data to prepare it for model development. Model Development : Build and train machine learning models using appropriate algorithms and techniques. Feature Engineering : Create relevant features and feature engineering pipelines to improve model performance. Model Evaluation : Evaluate model performance using appropriate metrics and validation techniques. Hyperparameter Tuning : Optimize model hyperparameters to achieve the best results. Deployment : Deploy machine learning models into production environments, ensuring scalability and reliability. Monitoring : Implement model monitoring and maintenance processes to ensure ongoing performance. Documentation : Maintain comprehensive documentation of AI/ML models, methodologies, and results. Research : Stay updated on the latest AI/ML research and technologies, and apply new insights to projects. Qualifications : Bachelor's degree in Computer Science, Data Science, or a related field (Master's degree preferred). Proven experience in AI/ML development, with a strong portfolio of projects. Proficiency in machine learning libraries and frameworks (e. g. , TensorFlow, PyTorch, scikit-learn). Strong programming skills in languages such as Python or R. Experience with data preprocessing, feature engineering, and model evaluation. Knowledge of deep learning, neural networks, and natural language processing (NLP) is a plus. Familiarity with cloud platforms (e. g. , AWS, Azure, GCP) and containerization (e. g. , Docker) is a plus. Excellent problem-solving and analytical skills. Effective communication and collaboration abilities. Ability to work independently and as part of a multidisciplinary team.