Your Team Responsibilities

• Designing and training machine learning models.
• Evaluating model performance and iterating for improvement.
• Collaborating with domain experts to refine AI solutions.
• Developing and optimizing algorithms for production use.
• Building scalable and efficient AI pipelines.
• Ensuring the reliability and robustness of deployed models.
• Translating research into practical applications
• Supporting AI initiatives by collaborating with other data scientists and engineers
• Essential for scripting, data manipulation, and working with ML frameworks.
• Using Docker and Kubernetes for deploying models in scalable environments
• Using Git for code management
• Explaining complex technical concepts to non-technical stakeholders

Your Key Responsibilities

• Designing and building AI models using suitable algorithms and frameworks.
• Training models with data and optimizing them for performance.
• Evaluating model performance using metrics like accuracy, precision, and recall.
• Collecting and preprocessing data to ensure quality and relevance.
• Cleaning data to handle missing values and inconsistencies.
• Creating and optimizing algorithms to solve specific problems.
• Experimenting with different model architectures and hyperparameters.
• Deploying AI models into production environments.
• Integrating models with existing systems and ensuring scalability.
• Monitoring model performance in real-time.
• Updating models as needed to maintain accuracy and efficiency
• Identifying business problems that can be solved with AI.
• Collaborating with stakeholders to define project scope and requirements.
• Staying updated with the latest AI trends and technologies.
• Conducting research to improve existing models and develop new solutions.

Your skills and experience that will help you excel

• LLMs and RAGs
• Transformers
• Machine Learning/Deep Learning/Neural Networks
• NLP
• Python
• Designing
• Problem Solving
• Cloud Computing