At a Glance
- Tasks: Join our Core ML team to build and maintain innovative machine learning models.
- Company: Depop, a leading fashion resale platform with a collaborative culture.
- Benefits: Health benefits, flexible working, generous leave, and professional development opportunities.
- Why this job: Make a real impact in the fashion industry with cutting-edge machine learning solutions.
- Qualifications: Proven experience in machine learning, strong Python skills, and leadership abilities.
- Other info: Enjoy a dog-friendly office and the chance to work abroad for 4 weeks each year.
The predicted salary is between 48000 - 84000 £ per year.
Depop is looking for a Senior Machine Learning Scientist to join our new Core ML team in the UK. You will work alongside a cross-functional team of Product Managers, ML Engineers, and fellow ML Scientists, helping build and maintain foundational machine learning models and infrastructure, such as product matching models, image embedding services, and lightweight classifiers, that support multiple product and marketing use cases across Depop. As a senior member of the team, you will be expected to take ownership of high-impact projects, lead technical direction on core modelling efforts, and mentor others while working across multiple domains and stakeholders.
Responsibilities
- Research, design, and deliver robust machine learning solutions to solve cross-cutting problems within the fashion resale space.
- Work with and fine-tune models for representation learning, computer vision, and classification, and lead efforts to productionise and scale them.
- Identify and define requirements from multiple stakeholders across the business, and lead the design of general-purpose machine learning solutions that power features like content understanding, moderation, and personalisation.
- Set up and conduct large-scale experiments to test hypotheses and guide model and product improvements, ensuring statistical rigour and real-world applicability.
- Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and help shape the long-term technical strategy for the team.
- Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping.
- Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders.
Qualifications Skills and Experience
- Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems.
- Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow.
- Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles.
- Ability to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members.
- Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders.
Bonus Points
- Experience with NLP, image classifiers, deep learning, or large language models.
- Experience with experiment design and conducting A/B tests.
- Experience building shared or platform-style ML systems.
- Experience with Databricks and PySpark.
- Experience working with AWS or another cloud platform (GCP/Azure).
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!
Senior Machine Learning Scientist - Core ml employer: Depop
Contact Detail:
Depop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Scientist - Core ml
✨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 might just get your application noticed.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your machine learning projects, especially those related to computer vision or NLP. This will help you stand out during interviews and showcase your hands-on experience.
✨Tip Number 3
Practice makes perfect! Brush up on your technical communication skills. Be ready to explain complex ML concepts in simple terms, as you'll need to engage with both techies and non-techies at Depop.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Depop team.
We think you need these skills to ace Senior Machine Learning Scientist - Core ml
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Scientist role. Highlight your experience with machine learning models, Python skills, and any relevant projects you've led. We want to see how your background aligns with what we're looking for!
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 you can contribute to our Core ML team. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Technical Skills: In your application, don't forget to showcase your technical skills, especially in frameworks like PyTorch or TensorFlow. We love seeing examples of your work, so if you have a portfolio or GitHub, include that too!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Depop
✨Know Your Models Inside Out
Make sure you can discuss your experience with machine learning models in detail. Be prepared to explain how you've built, fine-tuned, and scaled models in production settings, especially using frameworks like PyTorch or TensorFlow.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, be ready to share examples of how you've successfully collaborated with product managers and engineers. Highlight any experiences where you aligned technical approaches with business needs.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Brush up on your understanding of representation learning, computer vision, and classification. You might also want to prepare for questions about experiment design and A/B testing.
✨Communicate Clearly and Confidently
Practice explaining complex concepts in simple terms. You'll need to communicate findings to both technical and non-technical audiences, so being able to articulate your thoughts clearly is key. Consider doing mock interviews to refine this skill.