Senior Machine Learning Operations Engineer (ML Ops)

Job Description

We’re on a mission to provide equitable access to economic opportunity, for everyone.

We close critical skill gaps in the workforce through a new kind of apprenticeship that combines work and learning. We begin by recognizing high-potential individuals both inside and outside of a company's current workforce and then we create applied, guided and equitable learning programs, with measurable impact. Because we believe the world needs a better way to match its potential.

We work with over 1,500 leading companies including the likes of Microsoft, Citi and Just Eat to help solve their business-critical problems, and we’ve trained over 16,000 professional apprentices in the tech and data skills of the future. This is made possible by our global team who are driven to achieve a mission that matters, together.

Join Multiverse and help us set a new course for work.

As a Senior Machine Learning Operations Engineer (MLOps), you will be responsible for developing and maintaining Multiverse’s Machine Learning pipeline - establishing, automating, optimising and securing data flows from, through and into multiple data sources that our AI Team will use to serve all parts of the business.

This role will be within the AI Team, working closely with other ML Engineers, Data Scientists, ML Ops Engineers, Product Managers. While your primary focus will be on MLOps, you will also be asked to support the team with its broader Infrastructure & DevOps needs. The AI Team’s mission is to build the intelligence layer at Multiverse that fuels captivating educational experiences, drives effective and continuous digital transformation for enterprises, and empowers Multiverse coaches and operations with tools that scale our teaching capabilities.

You will need to be methodical, analytical, creative and tenacious with very high attention to detail. And while this is a technical role, our team culture is one where everyone is expected to collaborate well and take ownership of both deliverable & stakeholder management.

What you’ll focus on:

* Designing, automating, developing and maintaining our infrastructure, pipelines, and development processes that enable greater operational efficiency

* Deploying, managing, and optimizing AI solutions in production environments, ensuring smooth integration and efficient operations

* Experiment with data science and machine learning techniques to adapt AI solutions for production applications

* Creating systems for deployment, CI/CD, testing, and monitoring

* Identify and address system integrity and security risks

What we’re looking for:

Required:

* 5+ years of relevant MLOps experience in a production engineering environment

* Strong foundations in software engineering, building ML models, and DevOPs

* Deep Experience with Azure, e.g. API management, ML stack or a willingness to up-skill.

* Experience coding at production level with Python

* Experience with multiple cloud environments, PostgreSQL, GitHub, CircleCI/Jenkins (or similar), CI/CD and Infrastructure as Code (e.g. Terraform)

* Experience with model experiment tracking

* Commitment to Multiverse’s mission and values

You will most likely thrive and enjoy this role if:

* You have a meticulous attention to detail

* You are an exceptional communicator (especially cross-functionally), with an ability to translate technical concepts to the appropriate level of detail to the right audience

* Take a tenacious, curious, and pragmatic approach to problem solving, with a focus on generating usable and scalable outputs

* Enjoy having a lot of ownership to build services, processes, and infrastructure from scratch

* Pride yourself in having a growth mindset, being coachable, and learning every day