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, and health support for your well-being.
- Other info: Collaborative environment with opportunities for personal and professional growth.
- Why this job: Make a real impact in circular fashion while working with cutting-edge technology.
- Qualifications: Experience in machine learning and proficiency in Python required.
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, and in 2021 became a wholly-owned subsidiary of Etsy.
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.
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 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, offering generous benefits such as 25 days of annual leave, flexible working options, and opportunities for professional growth through mentorship and learning budgets, Depop fosters a culture of innovation and collaboration. Located in London, employees enjoy a dynamic atmosphere where creativity thrives, making it an ideal place for those passionate about circular fashion and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Depop. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repository showcasing your machine learning projects. This is your chance to demonstrate what you can do beyond the CV.
✨Tip Number 3
Get ready for the interview! Research Depop’s mission and values, and think about how your experience aligns with their goals. Be prepared to discuss how you can contribute to making fashion circular.
✨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.
We think you need these skills to ace Machine Learning Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Scientist role. Highlight relevant experience and skills that match the job description, especially your work with machine learning models and frameworks like PyTorch or TensorFlow.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about circular fashion and how your skills can contribute to Depop's mission. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any interesting machine learning projects, make sure to mention them! Include links to your GitHub or any relevant portfolios that demonstrate your coding skills and problem-solving abilities.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
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 related to ranking models and NLP. Be ready to discuss your past projects and how you've applied frameworks like PyTorch or TensorFlow in real-world scenarios.
✨Understand Depop's Mission
Familiarise yourself with Depop's mission to make fashion circular. Think about how your skills as a Machine Learning Scientist can contribute to this goal and be prepared to share your thoughts during the interview.
✨Prepare for Technical Questions
Expect technical questions that may involve coding challenges or problem-solving scenarios. Practise writing clean, production-grade Python code and be ready to explain your thought process clearly, especially when discussing data engineering and MLOps.
✨Show Your Collaborative Spirit
Depop values teamwork, so be ready to demonstrate your ability to work with cross-functional teams. Share examples of how you've collaborated with both technical and non-technical stakeholders in the past, highlighting your communication skills and humility.
