Participate in the design, development, and deployment of advanced machine learning models and algorithms to solve complex business challenges.
Apply expertise in Generative AI to develop and fine-tune models, contribute to synthetic data generation and data augmentation efforts, and engineer GenAI agents using both commercial and open-source LLMs.
Collaborate closely with domain experts, software engineers, and stakeholders to understand business requirements and translate them into actionable AI solutions.
Conduct exploratory data analysis, data preprocessing, and feature engineering to ensure high-quality input for modeling.
Stay at the forefront of AI research, experimenting with emerging techniques and staying informed about the latest advancements in the field.
Communicate findings, insights, and technical concepts to both technical and non-technical audiences through clear visualizations and presentations.
Contribute to developing and maintaining a robust machine learning infrastructure and best practices within the organization.
Requirements & Skills:
Completion or in progress to attain a degree in Computer Science, Statistics, Data Science, or a related field.
Experience in data science machine learning and generative AI.
Proficiency in writing and testing Python object-oriented code with hands-on experience with machine learning libraries and frameworks.
Strong understanding of deep learning frameworks (e.g., TensorFlow, PyTorch) and hands-on experience in implementing complex AI models.
Passion for the scientific process with knowledge and experience in AI system design, measurement, and testing techniques
Excellent problem-solving skills, analytical thinking, and the ability to approach complex challenges creatively.
Strong verbal and written communication skills to effectively collaborate with cross-functional teams and convey technical concepts to non-technical stakeholders.
Exposure to cloud computing platforms (AWS, Azure, GCP) and distributed computing is a plus.
