Role Overview & Mandate
Executive Summary
We are Multiverse, a tech scaleup with a social mission. We’re creating a diverse group of future leaders by building an outstanding...
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We are Multiverse, a tech scaleup with a social mission. We’re creating a diverse group of future leaders by building an outstanding alternative to university and corporate training, through the power of professional apprenticeships.
We’re one of the fastest-growing businesses in Europe and rapidly expanding in North America, working with over 500 clients including Facebook, KPMG, Morgan Stanley and the NHS. In June 2022, we broke the EdTech funding record (again!) by announcing our $220m Series D, making Multiverse the UK’s first ever EdTech unicorn.
Join us on our journey to democratising access to the best careers and learning opportunities.
The Opportunity
As a Senior Machine Learning Operations (MLOps) Engineer, 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 Data Science team will use to serve all parts of the business via Machine Learning.
This role will be within the Data Engineering & Infrastructure team but will involve very close collaboration with our Data Science team. Both of these teams sit within our broader Data & Insight department, which also includes Data Product Management, Analytics Tools, Solutions and Insight teams. While your primary focus will be on MLOps, you will also be required to support the team with its broader Infrastructure & DevOps needs.
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:
MLOps
Designing, automating, developing and maintaining our MLOps pipelines and processes to assist our Data Scientists in productionising their models
CI/CD, testing and monitoring of models
Managing versions and experiment /registry tracking
Management of a Data Version Control system
Establishing and maintaining good governance practices for MLOps
Infrastructure Management
Managing deployment via an Infrastructure as Code (Terraform) approach of AWS and other relevant resources
Continuously monitoring system integrity and security risks
Integration and Security
Assist with monitoring system integrity/security risks and implementing remediations/upgrades as necessary
Participating in regular infrastructure security reviews and overseeing implementation of all resultant technical change requirements
Working with the Data Engineers to ensure that timely, concise and accurate data is fed to our Data Science Lab and is used appropriately.
Automation, Optimisation and Scalability
Designing, developing and maintaining automated systems and processes (e.g. via AWS) that enable greater operational efficiency at scale
Ensuring all of our infrastructure is scalable - including management of any associated technical upgrades - ahead of organisational growth trajectory
Continuously monitoring for data accuracy
What we’re looking for:
Required:
3+ years of relevant MLOps experience
3+ years experience of working with a Data Science team
3+ years experience of working with Data Engineers
Proven track record of producing high quality Machine Learning deliverables against ambitious goals and deadlines
Pragmatic, ‘can-do’ approach with a demonstrable record of turning challenges into opportunities
Experience with AWS (inc RDS, S3, Athena, Sagemaker etc.), PostgreSQL, GitHub, CircleCI/Jenkins (or similar), ETL, CI/CD and Infrastructure as Code (e.g. Terraform)
Experience with model experiment tracking
Meticulous attention to detail
Commitment to Multiverse’s mission and values
Non-Required (But Desirable):
Experience with Asana (or similar) to manage quarterly/ongoing deliverables
Working knowledge of Python
Experience within education/skills sector
Benefits
Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company-wide wellbeing days
Health & wellbeing - private medical Insurance with Bupa, a medical cashback scheme, life insurance, and access to Spill - all in one mental health support
Hybrid & remote working - weekly or monthly visits to the London office
You have the opportunity to share in the business’ success (depending on your level)
Team fun - weekly socials and regular offsite events
Our commitment to Diversity, Equity and Inclusion
We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change.
Safeguarding
All posts in Multiverse involve some degree of responsibility for safeguarding. Successful applicants are required to complete a Disclosure Form from the Disclosure and Barring Service ("DBS") for the position. Failure to declare any convictions (that are not subject to DBS filtering) may disqualify a candidate for appointment or result in summary dismissal if the discrepancy comes to light subsequently.
