AI/Deep Learning Engineer

Job Summary:As a Junior AI/Deep Learning Engineer, you will collaborate with senior engineers and data scientists to design, build, and optimize AI/ML models with a focus on deep learning applications. This role is ideal for someone passionate about artificial intelligence, eager to work on innovative projects, and enthusiastic about applying machine learning to solve real-world problems.Key Responsibilities:Assist in the design, training, and evaluation of machine learning and deep learning models.Work with large datasets to preprocess, clean, and prepare data for modeling.Support in implementing neural networks, computer vision, and NLP models.Collaborate with data scientists, software engineers, and product teams to integrate AI solutions into applications.Help in debugging, tuning hyperparameters, and optimizing models for accuracy and performance.Stay updated on the latest AI/ML frameworks, tools, and research trends.Contribute to model documentation, experiment tracking, and reporting results.Participate in testing, validation, and deployment of AI/ML systems.Required Skills & Qualifications:Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.Proficiency in at least one programming language (Python, C++) with experience in AI/ML libraries (e.g., TensorFlow, PyTorch, Keras, Scikit-learn).Strong understanding of machine learning fundamentals and deep learning architectures (CNNs, RNNs, Transformers, etc.).Basic knowledge of data preprocessing, statistics, and probability.Familiarity with cloud platforms (AWS, GCP, Azure) for model deployment is a plus.Strong analytical and problem-solving skills.Good teamwork and communication abilities.Prior exposure through internships, projects, or research work in AI/ML is a plus.Benefits:Competitive salary and benefits package.Mentorship from experienced AI/ML professionals.Hands-on experience with cutting-edge AI frameworks and tools.Opportunities for career growth in AI, ML, and Data Science.Access to training resources, research papers, and workshops.Flexible working hours and innovative work culture.