Machine Learning Operations Engineer

Job Description

Job Purpose and primary objectives:

We are a data driven organisation, building scalable platforms and processes that accelerate how we use machine learning to solve difficult customer and business problems. 

As part of the Back End Engineering Fellowship, you will be working with API engineering, Data science and platform engineering teams to help drive our machine learning operations, increase our Machine Learning Test Score and platform maturity levels. 

You will be deploying, measuring, and maintaining our models and continuously improving our production workload ML pipelines and processes in the relentless pursuit of mastering the themes of automation and reliability. 

Key responsibilities:

• Produce high-quality, reliable machine learning model pipelines and continuously deliver and test them with a high degree of automation in the cloud. 
• Reduce manual steps and increase the velocity of experiments by reducing the time between data collection, model training, deployment, and feedback cycles. 
• Address infrastructure provisioning requirements and manage cloud resources and services. 
• Own complex tasks in the backlog and deliver them routinely with no significant issues. 
• Demonstrate responsibility for the entire team’s objectives. 
• Progress work consistently without significant need for support from more senior colleagues. 
• Solve problems collaboratively, communicating decisions through tech-talks and white-boarding sessions. 
• Deliver high-quality software design through proficiency in design patterns, algorithms, and data structures. 
• Help other engineers to produce clean, quality code through code reviews and pair programming. 
• Engage with product colleagues to improve value for the customer and to understand ambiguous requirements. 
• Approach and contribute to product planning and roadmap with an agile mindset. 
• Demonstrate and champion pragmatism in terms of commercial delivery and software quality. 
• Support the technical platform out of hours as a member of the support rota. 
• Evangelise technology, values, and ways of working within the team and wider software engineering community. 
• Contribute actively to Fellowships and Orchestras with a focus on positive momentum. 
• Coach, mentor and develop lesser experienced engineers. 
• Lead and take responsibility for initiatives to support senior colleagues. 
• Assist with recruitment and new starter onboarding activities. 

Key Skills/Knowledge:

• Azure Cloud Native Services 
• Databricks, Kubeflow, Azure ML, MLFlow 
• Azure Data Lake Store, Azure Data Factory 
• Kubernetes, Docker, Python microservices 
• Kafka, MongoDB, Redis 
• Concourse, GitHub Actions, Azure DevOps 
• Terraform, New Relic, PagerDuty