Fresh Jobs at Interswitch

Job Summary

• The Customer Success Executive role is that of providing L1 support to customer service requests via non-voice channels, using the incident management and request fulfilment processes, in line with Service Desk objectives.

Key Responsibilities

• Handle Complaints: Provide appropriate solutions and alternatives within the SLA and follow up to ensure resolution.
• Resolve Product or Service Problems:
  • Clarify the customer's complaint.
  • Determine the cause of the problem.
  • Select and explain the best solution.
  • Expedite correction or adjustment.
  • Follow up to ensure resolution via email, customer service portal, social media, and other non-voice channels.
• Understand Customer Requests: Provide accurate, valid, and complete information using appropriate methods/tools to achieve a satisfying outcome.
• Adhere to Communication Standards: Follow communication procedures, guidelines, and policies while using customer-focused metrics to achieve desired outcomes.

Ownership and Initiative

• Timely Escalation: Escalate issues to Level 2 support on time.
• Case Ownership: Retain ownership of issues until resolved, mitigated, or transferred to a new owner.
• Accountability for Outcomes: Focus on delivering timely and high-quality performance.

Broad Product/Service Understanding

• Basic Knowledge of Interswitch Products: Includes transaction processing services, settlement, dispute resolution, reporting, and incident management.
• Customer Usage Awareness: Understand how customers use these services to support them effectively.
• Postilion S1 Portal Knowledge: Ability to query transactions, identify issues, and troubleshoot.
• Continuous Learning: Stay updated on new and changing products or services.

Continual Service Improvement

• Learn and Adapt: Improve based on past successes and failures; embrace smarter, more focused approaches.
• Process Efficiency Awareness: Understand the importance of optimizing processes.
• Support Improvement Activities: Align expectations with process improvement initiatives.

Performance Management

• Task Prioritization: Focus on tasks that align with business needs.
• Impact Measurement: Measure work impact to ensure services remain available to customers.
• Timely Performance Delivery: Take ownership and accountability for delivering quality outcomes.

Essential Duties & Responsibilities

• Perform additional duties as assigned by your Line Manager

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Job Summary

• We are seeking a highly skilled AI/MLOps Developer to join our team. The ideal candidate will have a strong background in machine learning operations, model deployment, and managing ML pipelines. This role requires a deep understanding of AI/ML workflows and the ability to optimize and maintain AI models in production.

Key Responsibilities

• Model Development and Deployment: Design, develop, and deploy machine learning models into production environments, ensuring scalability and reliability.
• Pipeline Automation: Build and maintain automated ML pipelines to streamline model training, testing, and deployment processes.
• Monitoring and Optimization: Monitor deployed models for performance and accuracy, implementing retraining and optimization strategies as needed.
• Infrastructure Management: Manage cloud-based and on-premise infrastructure to support the training and deployment of ML models, ensuring cost efficiency and scalability.
• Security and Compliance: Implement and maintain robust security practices to protect sensitive data and ensure compliance with relevant regulations.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders to integrate ML models into applications and systems.
• Documentation: Maintain comprehensive documentation of ML pipelines, deployment processes, and model performance metrics.
• Continuous Improvement: Stay updated with the latest advancements in AI/ML and DevOps practices, and apply this knowledge to improve existing systems and processes.
• Troubleshooting: Identify and resolve issues related to model deployment, performance, and infrastructure on time.

Required Qualifications

• Education: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• Experience: Proven experience in AI/MLOps or a similar role, with hands-on experience in deploying and managing machine learning models.

Technical Skills:

• Proficiency in programming languages such as Python, and familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Experience with containerization and orchestration tools such as Docker and Kubernetes.
• Knowledge of cloud platforms (AWS, Azure, GCP) and their ML services.
• Familiarity with CI/CD tools and processes for ML pipelines.
• Strong understanding of version control systems (e.g., Git, BitBucket).
• Experience with monitoring and logging tools for model performance tracking.

Preferred Qualifications

• Experience with advanced topics like distributed training, model explainability, and ethical AI considerations.
• Familiarity with data engineering practices and tools like Apache Spark or Hadoop.
• Contributions to open-source projects related to AI/MLOps.
• Understanding of software development best practices, including Agile methodologies.