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Python Developer
3 months ago
We are seeking an experienced Data Engineer with a strong background in Python, AI/ML (Artificial Intelligence/Machine Learning), and secondary expertise in Genesys. The ideal candidate will be responsible for designing and implementing robust data pipelines, developing machine learning models, and integrating AI-driven insights into business processes. Additionally, you will support and enhance our contact center operations by leveraging your knowledge of Genesys. This role requires a combination of advanced data engineering skills and practical AI/ML experience, along with the ability to work in a dynamic, cross-functional team.
Key Responsibilities:Data Engineering:
- Design, develop, and maintain scalable data pipelines to process and analyze large datasets.
- Collaborate with data scientists and analysts to deploy machine learning models into production.
- Implement data storage solutions (e.g., data lakes, warehouses) and optimize them for performance.
- Ensure data quality, integrity, and security across all data engineering activities.
- Monitor and troubleshoot data pipelines to ensure reliability and efficiency.
AI/ML Development:
- Develop and deploy AI/ML models using Python and relevant frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Collaborate with cross-functional teams to integrate machine learning models into business applications.
- Perform feature engineering, model training, validation, and tuning.
- Monitor model performance in production and continuously improve accuracy and efficiency.
- Stay up-to-date with the latest advancements in AI/ML and implement best practices.
Genesys Integration (Secondary):
- Support the integration of AI-driven insights with Genesys contact center solutions.
- Develop and maintain custom scripts and workflows within the Genesys environment.
- Collaborate with the contact center team to optimize customer interactions using data-driven approaches.
- Troubleshoot and resolve issues related to Genesys applications and integrations.
- Provide technical guidance and support to teams using Genesys.
- Collaboration & Communication:
- Work closely with data scientists, software engineers, and business stakeholders to deliver data-driven solutions.
- Communicate complex technical concepts to non-technical stakeholders in a clear and understandable manner.
- Document technical solutions and processes to ensure knowledge sharing and continuity.
- Education:
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field. A Master’s degree is preferred.
- Experience:
- Minimum of 4-6 years of experience in data engineering, with a focus on AI/ML model development and deployment.
- Proven experience with Python for data processing and machine learning tasks.
- Strong understanding of AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with data storage and processing technologies (e.g., SQL, NoSQL, Hadoop, Spark).
- Hands-on experience with Genesys platforms (e.g., PureConnect, PureCloud) and contact center integration.
- Skills:
- Proficiency in Python and relevant data engineering/AI libraries.
- Strong understanding of machine learning concepts, algorithms, and best practices.
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for data and AI/ML workloads.
- Ability to design and implement scalable and reliable data pipelines.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication skills and ability to work collaboratively within a team.
- Experience with big data technologies (e.g., Apache Kafka, Hadoop, Spark).
- Familiarity with DevOps practices and CI/CD pipelines for AI/ML deployment.
- Knowledge of advanced AI/ML techniques, such as deep learning, NLP, and reinforcement learning.
- Certification in Genesys or relevant data engineering/AI certifications.
- Competitive salary and comprehensive benefits package.
- Opportunity to work on cutting-edge AI/ML and data engineering projects.
- A collaborative and innovative work environment with opportunities for growth and development.
- Continuous learning and professional development opportunities.