Sumo Logic is a cloud-native SaaS data analytics platform that solves complex observability and security problems. Customers choose our product because it allows them to easily monitor, optimize, and secure their applications, systems, and infrastructures. 

Our microservices architecture hosted on AWS ingests petabytes of data daily across many geographic regions. Millions of queries a day analyze hundreds of petabytes of data.

What can you expect to do?

We are looking for a dedicated Software Engineer focused on Machine Learning Principles to ensure the integrity and performance of our ML models. You will help with building data sets, adding validation metrics, helping MLE's to scale up, setting up model building & evaluation frameworks 

This is a vital role that requires a deep understanding of data quality, consistency, and the ability to anticipate data needs for robust testing of model solutions.

Responsibilities

• Identifying and validating opportunities for the application of AI/ML or data-driven techniques
• Driving technical delivery through the full feature lifecycle, from idea to production and operations
• Collaborating within and beyond the team to identify problems and deliver solutions 
• Assessing requirements and approaches for large-scale data and AI/ML platform components
• Developing supporting tooling, automation, and microservices to accelerate the team

Requirements

• Having experience of 1-2+ years in testing around ML models
• Bachelor’s or master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Good understanding of machine learning concepts and model training processes 
• Experience with data visualization tools and techniques.
• Demonstrable skill in SQL and working knowledge of database technologies.
• Solid understanding of statistical methods and their application in validating and testing ML models.
• Familiarity with version control systems like Git, and CI/CD tools such as Jenkins or Travis CI.
• Strong analytical and critical thinking skills with a problem-solving mindset.

Preferred Skills

• Previous experience collaborating with data science teams and leveraging their datasets in a testing environment.
• Experience with Docker, Kubernetes, or similar container and orchestration platforms is advantageous.
• Exceptional attention to detail and a passion for achieving data accuracy through rigorous testing.
• Experience with modern DevOps monitoring and deployment/rollout technologies.