Senior Machine Learning Engineer

Depop • Full-time • London, GB • 2d ago

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.

The Role

At Depop, machine learning is integral to our value proposition.In the ranking team, we build learning-to-rank models that power personalised experiences across the Depop app (in search results, recommendations, etc.).

The team is currently made of 3 Machine Learning Scientists and 1 Machine Learning Engineer. It owns a series of models deployed in SageMaker for real-time inference. These models are called in by various services across the app (e.g. the search service to rank results coming from our vector database in OpenSearch), serving millions of personalised results to users daily.

We are looking for a dedicated Senior Machine Learning engineer to join our Ranking team. As part of this team, you will participate in building, deploying and monitoring the future ranking models that will improve user experience across the app.

Responsibilities

Design and implement pipelines for training, deploying & monitoring real-time ranking models, in collaboration with the other ML Engineer(s) in the team.
Work closely with ML Scientists in the ranking team on the experimentation and deployment of new models.
Collaborate with Backend Engineers from “client services” (e.g. search service, which calls one of the real-time models) to define requirements and plan future experiments.
Help design and build the ML platform at Depop in collaboration with the MLOps infrastructure team, working on various areas:
- Robust prototyping & training of models
- CI/CD pipelines for model deployments
- Model serving for real-time and batch implementations
- Improving our feature store to serve features offline/online
- Monitoring & alerting
Hold high standards for operational excellence; from running your own services to testing, monitoring, maintenance and reacting to production issues.
Contribute to a strong engineering culture in the ML group, orientated on technical innovation, and professional development.

Requirements

Consistent track record of building pipelines to train & deploy ML models and contributing to an ML platform
Experience with the core concepts of data science / ML workflows
A strong sense of ownership, autonomy and a highly organised nature.
Outstanding communication skills, especially in taking care of multiple stakeholders
Solid understanding of systems design within a modern cloud-based environment (AWS, GCP)

Technologies and Tools

Python
Data science / ML / MLOps tooling: e.g. Sagemaker, Databricks, TFServing and more
Common ML libraries: scikit-learn, pytorch/tensorflow, mlflow etc.
Spark & DataBricks
AWS - IAM, S3, redis, ECS and more
Shell scripting and related tooling
Good working understanding of continuous integration/deployment tools and practices
Experience with streaming and/or batch-based systems supporting data integrations to third-party platforms (e.g. using Kafka, Airflow, RMQ, etc.)

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