AI/ML Developer

Overview: The AI/ML Developer plays a critical role in the organization's efforts to leverage machine learning and artificial intelligence to develop innovative solutions. They are responsible for designing, implementing, and maintaining machine learning and deep learning algorithms to drive key business initiatives. Key Responsibilities: Collaborate with cross-functional teams to identify and define machine learning tasks Develop models and algorithms for natural language processing, computer vision, and predictive analytics Collect, clean, and preprocess large datasets for model training and evaluation Build scalable machine learning pipelines and frameworks Implement and optimize machine learning models in production environments Conduct performance analysis and fine-tune models to improve accuracy and efficiency Stay updated with the latest advancements in AI/ML and integrate new technologies into existing systems Collaborate with the data engineering team to ensure seamless data flow for model training and deployment Participate in code reviews and contribute to the continuous improvement of the AI/ML development process Provide technical guidance and mentorship to junior members of the AI/ML team Required Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field Proven experience in developing and deploying machine learning models using Python and popular libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms, neural networks, and deep learning techniques Proficiency in data analysis, feature engineering, and model evaluation Experience with cloud platforms for AI/ML deployment (e.g., AWS, Azure, GCP) Familiarity with version control systems, such as Git Strong problem-solving skills and the ability to work on complex, large-scale problems Excellent communication and collaboration abilities to work effectively in a team environment Experience with deploying machine learning models in production environments Ability to interpret and present complex technical information to non-technical stakeholders