Senior Machine Learning Operations Engineer
Multiverse
This job is no longer accepting applications
See open jobs at Multiverse.See open jobs similar to "Senior Machine Learning Operations Engineer" General Catalyst.We’re on a mission to create a diverse group of future leaders. We do that through professional apprenticeships because we believe learning on-the-job creates a more equitable and successful path to careers. We find, train and support talented individuals, wherever they are in their career journey, and equip them with the in-demand tech, software engineering, and data skills to transform their careers and deliver a better route to growth for their employers.
We’ve had some big achievements. We hit 10,000 apprentices in our community - and counting. We launched one of the largest data apprenticeship programs in the UK with Jaguar Land Rover, and we’ve partnered with companies like Mars, Verizon and CitiBank. Not to forget becoming a mission-driven EdTech unicorn after our $220m Series D.
But we aren’t stopping here. Join Multiverse and build the future of learning at work.
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
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 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 multiple cloud environments, 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):
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 and 8 bank holidays per year
Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health support
Hybrid & remote work offering - with weekly or monthly visits to the London office and the opportunity to work abroad 45 days a year
Team fun - weekly socials, company wide events and office snacks!
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.
This job is no longer accepting applications
See open jobs at Multiverse.See open jobs similar to "Senior Machine Learning Operations Engineer" General Catalyst.