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 Etsy. Find out more at www.depop.com
Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome, no matter who they are or where they’re 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. We’re 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. We’re 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 adjustments@depop.com. For any other non-disability related questions, please reach out to our Talent Partners.
At Depop, machine learning is integral to our value proposition. We are looking for a Senior MLOps engineer to help level-up how ML solutions are delivered at Depop.
As a Senior MLOps engineer sitting in the central MLOps team, you will be responsible for enabling our ML Scientists - currently spread across five product functions - to deliver value by providing self-serve platforms and services for ML model + feature development, deployment and monitoring.
Do you find happiness in providing tooling, services and platforms that help businesses untap the enormous value of machine learning? If so, this could be the perfect match.
Want to find out more about Depop & our engineering team? We write about technology, people and smart engineering right here -https://engineering.depop.com/
Leading on the design, implementation and maintenance of tooling + platforms for:
Productionising model training workflows
ML feature engineering and deployment
Deploying, monitoring and managing ML models in production
Model performance monitoring and drift detection
Model retraining, rollback, and continuous improvement
Playing an enablement role by working closely with ML Scientists and Backend Engineers whilst also finding opportunities to improve the velocity + reliability of the ML model deployment cycle.
Proactively identify pain points and make improvements that help increase your team’s efficiency.
Using your extensive domain knowledge + relationships with key stakeholders to positively influence the direction of the team.
Setting the team’s standards for operational excellence; from running your own services to testing, monitoring, maintenance and reacting to production issues.
Adding to a strong engineering culture orientated on technical innovation, continuous improvement and professional development.
Mentoring junior engineers to help them hit their career goals and add further value to Depop.
Consistent track record of leading on the successful end-to-end delivery of your projects; scoping and translating complex business/user requirements into plans, with a focus on MvP; design and implementation (including coordinating the effort of other engineers); and maintenance, with a strong emphasis on observability and handling failure modes.
Solid understanding of the ML lifecycle, from model training and evaluation to deployment and monitoring.
Strong programming skills in Python, with experience in ML libraries such as TensorFlow, PyTorch and Scikit-learn.
Experience working with ML training/inference platforms such as Databricks, SageMaker and Seldon.
Experience building CI/CD processes with tools such as Jenkins or GitHub Actions.
Exemplary communication skills, especially in dealing with multiple stakeholders.
Experience with cloud platforms (e.g., AWS, GCP, Azure), containerization (Docker, Kubernetes) and infrastructure-as-code (IaC) tools (Terraform, CloudFormation).
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!
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