Software Engineer Advisor (MLOpsEngineer)

AnMLOpsEngineer is responsible for deploying, monitoring, and maintaining machine learning models in production environments. This role bridges the gap between data science and IT operations, ensuring seamless integration of machine learning models into operational workflows. TheMLOpsEngineer works closely with data scientists, software engineers and DevOps teams to automate and streamline the model lifecycle, from development to deployment and monitoring.

In addition to Delivery, theMLOpsEngineer should have an automation first and continuous improvement mindset.Theyshould drive the adoption of CI/CD tools and support the improvement of the tools sets/processes.

Behaviors ofMLOpsEngineer:

Full Stack Engineersisable toarticulate clear business objectives aligned to technical specifications and work in an iterative, agile pattern daily. They have ownership over their work tasks, and embrace interacting with all levels of the team and raise challenges when necessary. We aim to be cutting-edge engineer – not institutionalized developers.

This position is withEvernorth, a new business within the Cigna Corporation

Keyduties and responsibilities

• Design, develop, and implementMLOpspipelines for the continuous deployment and integration of machine learning models.

• Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes.

• Automate the training, testing and deployment processes for machine learning models.

• Continuously monitor and maintain models in production, ensuring optimal performance, accuracy and reliability.

• Implement best practices for version control, model reproducibility and governance.

• Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.

• Troubleshoot and resolve issues related to model deployment and performance.

• Ensure compliance with security and data privacy standards in allMLOpsactivities.

• Keepup-to-datewith the latestMLOpstools, technologies and trends.

• Provide support and guidance to other team members onMLOpspractices.

Required Skills and Experience:

• 5+ yearsof experience inMLOps, DevOps or a related field.

• Strong understanding of machine learning principles and model lifecycle management

• Experience in implementing ML model monitoring techniques and tools

• Proficiency in programming languages such as Python,PySpark,Spark/Scala

• Hands-on experience in machine learningand deep learningframeworks likeSpark ML,TensorFlow,PyTorch, Scikit-learn

• 4+ years of solution architecting in cloud technology (eg.AWS, Azure, google cloud)and their respective machine learning services

• 4+ years of working experience with operationalizing Machine learning models

• 4+ years being part of Agile teams – Scrum or Kanban