At a Glance
- Tasks: Create innovative machine learning models to enhance user experience on Depop's app.
- Company: Join Depop, a vibrant community-driven fashion marketplace with over 35 million users.
- Benefits: Enjoy flexible working, generous leave, health support, and continuous learning opportunities.
- Other info: Be part of a diverse team that values different perspectives and fosters innovation.
- Why this job: Make a real impact in the fashion industry while working with cutting-edge technology.
- Qualifications: Experience in machine learning, Python proficiency, and a collaborative mindset are essential.
The predicted salary is between 60000 - 80000 £ per year.
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.
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. 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.
At Depop, machine learning is integral to our value proposition. As a Machine Learning Scientist, you will work on building state-of-the-art ranking models to power Depop’s app, serving millions of personalised results to users daily.
Responsibilities- Research, design and deliver machine learning solutions to tackle problems.
- Understand requirements from various stakeholders across the business, designing machine learning solutions to solve business problems.
- Set up and conduct large-scale experiments to test hypotheses and drive product development.
- Keep up to date with state-of-the-art research, contribute to Machine Learning groups, and apply new techniques for NLP, image processing, etc.
- Participate in team ceremonies (follow the agile cadence, technical whiteboarding sessions, product road mapping, etc).
- Report and present technical findings to technical and non-technical audiences.
- Experience working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problems.
- Solid understanding of machine learning concepts, familiarity working with common frameworks such as Transformers, PyTorch or TensorFlow.
- Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps.
- Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders.
- Passion for learning new skills and staying up-to-date with ML algorithms.
- Experience working on learning-to-rank, search or recommendation models.
- Experience with deep learning & large language models.
- Experience with experiment design and conducting A/B tests.
- Experience with Databricks and PySpark.
- Experience working with AWS or another cloud platform (GCP/Azure).
- Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa, subsidised counselling and coaching with Self Space, Cycle to Work scheme, 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.
- 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!
Machine Learning Scientist in London employer: Dormont Manufacturing Co
Depop is an exceptional employer that champions a diverse and inclusive work environment, reflecting the vibrant community it serves. With a strong focus on employee well-being, the company offers generous benefits such as 25 days of annual leave, flexible working options, and comprehensive health support, including mental health resources. Additionally, Depop fosters professional growth through learning budgets and mentorship programmes, making it an ideal place for Machine Learning Scientists to thrive and innovate in the heart of London.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Depop on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can make you stand out in interviews.
✨Tip Number 3
Get ready for the technical grill! Brush up on your ML concepts and be prepared to discuss your problem-solving approach. Practice explaining your thought process clearly, as you'll need to communicate with both techies and non-techies.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Depop community. Don’t miss out!
We think you need these skills to ace Machine Learning Scientist in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Scientist role. Highlight relevant experience, especially with machine learning frameworks like PyTorch or TensorFlow, and showcase any projects that demonstrate your skills in solving industry-scale problems.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with Depop's mission of making fashion circular. Don’t forget to mention your collaborative spirit and eagerness to learn!
Showcase Your Projects:If you've worked on any interesting machine learning projects, make sure to include them in your application. Whether it's a personal project or something from a previous job, showing off your hands-on experience can really set you apart from other candidates.
Apply Through Our Website:We encourage you to apply through our website for a smooth application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates regarding your application status!
How to prepare for a job interview at Dormont Manufacturing Co
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning concepts, especially those relevant to ranking models and NLP. Be ready to discuss your experience with frameworks like PyTorch or TensorFlow, and have examples of how you've applied these in real-world scenarios.
✨Understand Depop's Mission
Familiarise yourself with Depop's mission to make fashion circular and their community-driven approach. Show that you understand how machine learning can enhance user experience and contribute to this mission during your interview.
✨Prepare for Technical Questions
Expect technical questions that may involve coding challenges or problem-solving scenarios. Practice writing production-grade Python code and be prepared to explain your thought process clearly, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Show Your Collaborative Spirit
Depop values teamwork, so be ready to share examples of how you've worked collaboratively in the past. Highlight your ability to engage with cross-functional teams and how you’ve contributed to team ceremonies or agile processes.
