MLOps Engineering Manager
MLOps Engineering Manager
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Company Description
Depop is the community-powered circular fashion marketplace where anyone can buy sell and discover desirable secondhand fashion. With a community of over 35 million users Depop is on a mission to make fashion circular redefining fashion consumption. Founded in 2011 the company is headquartered in London with offices in New York and Manchester and in 2021 became a wholly-owned subsidiary of out more at
Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome no matter who they are or where theyre from. Just as our platform connects people globally we believe our workplace should reflect the diversity of the communities we serve. We thrive on the power of different perspectives and experiences knowing they drive innovation and bring us closer to our users. Were proud to be an equal opportunity employer providing employment opportunities without regard to age ethnicity religion or belief gender identity sex sexual orientation disability pregnancy or maternity marriage and civil partnership or any other protected status. Were continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.
If due to a disability you need adjustments to complete the application please let us know by sending an email with your name the role to which you would like to apply and the type of support you need to complete the application to . For any other non-disability related questions please reach out to our Talent Partners.
Job Description
We are looking for an experienced MLOps Manager to lead our growing MLOps function. Youll manage a team of 8 engineers and specialists set the strategic direction for how machine learning is developed deployed and scaled across Depop and ensure we are delivering robust secure and scalable ML infrastructure.
Our MLOps stack is modern cloud-native and carries very little tech debt giving us the freedom to focus on building rather than firefighting. This role comes with a wide span of control and genuine strategic agency youll be shaping the direction of how machine learning is built deployed and scaled across the business. Because Depop is deeply ML-driven this position isnt just about keeping the lights on; its central to how we deliver value to our users and to the business. Youll be empowered to set best practices influence architectural decisions and ensure that our teams can move quickly while maintaining trust reliability and impact.
This role combines technical leadership vendor management and strategic oversight and will require you to work closely with engineering product and data leadership to ensure machine learning drives real impact for Depop and our community.
Key Responsibilities
Team Leadership: Lead coach and develop a team of 8 MLOps engineers fostering a culture of high performance collaboration and growth.
Technical Leadership & Decision-Making: Provide guidance on architecture tooling and best practices for ML pipelines model deployment monitoring and incident management.
Collaboration with Applied ML Org: Partner closely with machine learning scientists ML management and cross-functional teams across the organisation to ensure MLOps solutions are aligned with scientific innovation business priorities and operational needs.
Strategic Direction: Define and deliver the MLOps strategy aligning with Depops broader Data and Engineering roadmap.
Vendor Management: Oversee operational relationships with external vendors ensuring service quality cost-effectiveness and alignment with team needs. Collaborate with Vendor Managers on contract negotiations renewals and vendor evaluations to ensure optimal long-term partnerships.
Leadership Reporting: Provide clear concise updates on progress risks and priorities in fortnightly leadership updates.
Incident Oversight: Act as an escalation point for ML/infra incidents ensuring rapid resolution and learnings captured.
Cross-Org Collaboration: Engage proactively with the Data org (data science data engineering analytics) to ensure MLOps solutions meet evolving business needs.
Requirements
Proven experience leading an MLOps ML Engineering or Platform Engineering team.
Deep-rooted enthusiasm for Platform disciplines
A background in Applied Machine Learning
Hands-on experience with cloud platforms (AWS GCP or Azure) including provisioning and managing ML infrastructure at scale.
Strong understanding of GPU computing for training and serving ML models.
Experience designing and managing containerised ML workloads (Docker Kubernetes Kubeflow or similar orchestration frameworks) and integrating with CI/CD tools (e.g. Jenkins GitHub Actions GitLab CI).
Familiarity with distributed data processing and ML training frameworks (e.g. Spark Ray TensorFlow Distributed or PyTorch Distributed).
Solid grasp of monitoring logging and observability for large-scale ML systems.
Knowledge of cost optimisation strategies for compute- and GPU-intensive workloads in cloud environments.
Excellent people leadership skills with experience managing and developing engineering teams.
Demonstrated ability to set strategy and drive execution in a fast-paced environment.
Strong communication skills with the ability to provide clear updates to technical and non-technical audiences.Proactive collaborative and comfortable engaging across multiple disciplines.
Nice to haves
Experience managing vendors contracts and budgets.
Experience with Databricks Tecton (or Feast) Seldon SageMaker
Additional Information
Health Mental Wellbeing
PMI and cash plan healthcare access with Bupa
Subsidised counselling and coaching with Self Space
Cycle to Work scheme with options from Evans or the Green Commute Initiative
Employee Assistance Programme (EAP) for 24/7 confidential support
Mental Health First Aiders across the business for support and signposting
Work/Life Balance:
25 days annual leave with option to carry over up to 5 days
1 company-wide day off per quarter
Impact hours: Up to 2 days additional paid leave per year for volunteering
Fully paid 4 week sabbatical after completion of 5 years of consecutive service with Depop to give you a chance to recharge or do something you love.
Flexible Working: MyMode hybrid-working model with Flex Office Based and Remote options *role dependant
All offices are dog-friendly
Ability to work abroad for 4 weeks per year in UK tax treaty countries
Family Life:
18 weeks of paid parental leave for full-time regular employees
IVF leave shared parental leave and paid emergency parent/carer leave
Learn Grow:
Budgets for conferences learning subscriptions and more
Mentorship and programmes to upskill employees
Your Future:
Life Insurance (financial compensation of 3x your salary)
Pension matching up to 6% of qualifying earnings
Depop Extras:
Employees enjoy free shipping on their Depop sales within the UK.
Special milestones are celebrated with gifts and rewards!
Required Experience:
Manager
Employment Type
Full-Time
