Responsibilities: 

- Collaborate with cross-functional teams to understand business requirements and identify opportunities for applying GenAI technologies. 

- Develop and implement machine learning models and algorithms for GenAI projects. 

- Perform data cleaning, preprocessing, and feature engineering to prepare data for analysis. 

- Collaborate with data engineers to ensure efficient data processing and integration into machine learning pipelines. 

- Validate and evaluate model performance using appropriate metrics and techniques. 

- Develop and deploy production-ready machine learning applications and solutions. 

- Utilize object-oriented programming skills to build robust and scalable software components. 

- Utilize Kubernetes for container orchestration and deployment. 

- Design and build chatbots using GenAI technologies. 

- Communicate findings and insights to stakeholders through data visualizations, reports, and presentations. 

- Stay up-to-date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data science processes. 

Requirements: 

- 3-5 years of relevant technical/technology experience, with a focus on GenAI projects. 

- Strong programming skills in languages such as Python, R, or Scala. 

- Proficiency in machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. 

- Experience with data preprocessing, feature engineering, and data wrangling techniques. 

- Solid understanding of statistical analysis, hypothesis testing, and experimental design. 

- Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. 

- Knowledge of data visualization tools and techniques. 

- Strong problem-solving and analytical skills. 

- Excellent communication and collaboration abilities. 

- Ability to work in a fast-paced and dynamic environment. 

Preferred Qualifications: 

- Experience with object-oriented programming languages such as Java, C++, or C#. 

- Experience with developing and deploying machine learning applications in production environments. 

- Understanding of data privacy and compliance regulations. 

- Relevant certifications in data science or GenAI technologies.