Staff Machine Learning Scientist, Ranking

Staff Machine Learning Scientist, Ranking

Full-Time 48000 - 84000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the design and deployment of advanced ranking models for Depop's app.
  • Company: Join a dynamic team at Depop, a leading platform in personalised recommendations.
  • Benefits: Enjoy flexible working, health benefits, and generous leave policies.
  • Other info: Mentorship opportunities and a supportive work culture await you.
  • Why this job: Make a real impact by innovating with cutting-edge machine learning techniques.
  • Qualifications: Proven experience in machine learning and strong programming skills in Python.

The predicted salary is between 48000 - 84000 £ per year.

Depop is looking for a talented Staff ML Scientist to join our Ranking 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 ranking models to power Depop's app, serving millions of personalised results to users daily. As a staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and mentor and coach others to drive innovation at scale, while working across multiple domains and stakeholders.

Responsibilities

  • Lead the design and deployment of advanced ranking models for Depop's entire app, covering personalised recommendations, search results and other surfaces.
  • Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes.
  • Lead the end-to-end lifecycle of ML projects: from ideation, data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration.
  • Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy.
  • Mentor, coach, and set technical direction within the Ranking ML team, helping others grow and innovate.
  • Act as a thought leader in the ranking space, sharing learnings internally, engaging with the wider ML community, and showcasing our work externally.

Qualifications

  • Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact.
  • Proven track record in designing and optimizing learning-to-rank models.
  • Deep understanding of machine learning concepts and frameworks.
  • Proven ability to productionize ML models and pipelines: from prototyping to deployment, with strong experience in monitoring, iteration, and troubleshooting.
  • Advanced programming skills in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.
  • Experience leading projects and mentoring engineers or scientists, with a track record of fostering team growth and technical excellence.
  • Excellent communication skills: able to bridge technical and non-technical stakeholders and influence decision making.
  • Committed to responsible AI practices, including attention to ethics, fairness, and inclusivity.

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.
  • 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!

Staff Machine Learning Scientist, Ranking employer: Depop

DEPOP is an excellent employer that fosters a collaborative and innovative work culture, where Senior iOS Engineers can thrive while leading architecture for impactful user experiences. Located in Greater London, employees enjoy flexible working options, comprehensive healthcare access, and generous leave policies, all of which support a healthy work-life balance. With opportunities for mentorship and professional growth, DEPOP is dedicated to empowering its team members to make meaningful contributions to the secondhand fashion marketplace.

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Contact Details:

Depop Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Machine Learning Scientist, Ranking

Tip Number 1

Network like a pro! Reach out to folks 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! If you've got a portfolio of projects or contributions to open-source, make sure to highlight them. It’s a great way to demonstrate your expertise in ML and ranking models.

Tip Number 3

Prepare for the interview by brushing up on your technical knowledge and soft skills. Be ready to discuss how you’ve led projects and mentored others, as these are key for a staff-level role.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!

We think you need these skills to ace Staff Machine Learning Scientist, Ranking

Machine Learning
Ranking Models
Data Acquisition
Feature Engineering
Model Training
Model Evaluation
Deployment of ML Models

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of Staff ML Scientist. Highlight your experience with ranking models and any leadership roles you've had. We want to see how your skills align with what we're looking for!

Showcase Your Projects:Include specific examples of ML projects you've led or contributed to. Detail the impact these projects had on business outcomes, as this will help us understand your ability to drive innovation at scale.

Be Clear and Concise:When writing your application, keep it clear and concise. Use straightforward language to explain complex concepts, as we value excellent communication skills that bridge technical and non-technical stakeholders.

Apply Through Our Website:We encourage you to apply through our website for a smoother process. This way, we can easily track your application and ensure it gets the attention it deserves!

How to prepare for a job interview at Depop

Know Your Models Inside Out

Make sure you can discuss your experience with designing and optimising learning-to-rank models in detail. Be ready to explain the challenges you faced, how you overcame them, and the measurable impact your models had on previous projects.

Showcase Your Collaboration Skills

Since this role involves working closely with cross-functional teams, prepare examples of how you've successfully collaborated with product managers, engineers, and data scientists. Highlight any specific projects where teamwork led to innovative solutions.

Demonstrate Your Leadership Abilities

As a staff-level member, you'll be expected to mentor others. Think of instances where you've led projects or coached team members. Be ready to discuss your approach to fostering growth and technical excellence within a team.

Stay Current with ML Trends

Research emerging machine learning techniques and frameworks relevant to ranking models. Be prepared to discuss how you would integrate these into Depop's app and contribute to the long-term product strategy, showcasing your thought leadership in the field.