Staff Machine Learning Scientist - Core ml
Staff Machine Learning Scientist - Core ml

Staff Machine Learning Scientist - Core ml

Full-Time 48000 - 72000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and develop machine learning solutions for the fashion resale space.
  • Company: Join Depop's innovative Core ML team in the UK.
  • Benefits: Flexible working, health benefits, generous leave, and professional development opportunities.
  • Why this job: Lead impactful ML initiatives and shape the future of fashion technology.
  • Qualifications: Experience in machine learning, Python, and collaboration with multi-functional teams.
  • Other info: Enjoy a dog-friendly office and opportunities for international work.

The predicted salary is between 48000 - 72000 £ per year.

Depop is looking for a Staff Machine Learning Scientist to join our new Core ML team in the UK. You will work alongside a multi-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 staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and coach others to drive innovation at scale, while working across multiple domains and partners.

Responsibilities
  • Own the design, development, and deployment of 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 own efforts to productionize, scale, and evolve them as shared systems.
  • Partner closely with senior stakeholders across the business to define problems, and lead the design of general-purpose, scalable ML solutions that power features like content understanding, moderation, and personalisation.
  • Lead the end-to-end lifecycle of large-scale experiments, from hypothesis generation through evaluation, to guide model and product improvements, ensuring statistical rigor and real-world applicability.
  • Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and contribute technical expertise to long-term product and data strategy.
  • Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping, setting technical direction and improving the team.
  • Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making.
Qualifications
  • Proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact.
  • 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 the end-to-end lifecycle of ML initiatives, work independently in ambiguous problem spaces, and mentor and grow other scientists and engineers.
  • Strong collaboration and interpersonal skills, with experience aligning technical approaches with multi-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!

Staff Machine Learning Scientist - Core ml employer: Depop

Depop is an exceptional employer that fosters a collaborative and innovative work culture, particularly within its new Core ML team in the UK. Employees benefit from a range of perks including flexible working options, generous leave policies, and comprehensive health support, all while having the opportunity to lead impactful machine learning initiatives that shape the future of fashion resale. With a strong emphasis on personal growth and mentorship, Depop empowers its staff to thrive both professionally and personally in a dynamic environment.
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Contact Detail:

Depop Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Staff Machine Learning Scientist - Core ml

✨Tip Number 1

Network like a pro! Reach out to current employees at Depop on LinkedIn or other platforms. 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! Get comfortable discussing your past projects and the impact they had. Be ready to explain your thought process and how you tackled challenges—this is key for impressing those senior stakeholders.

✨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 Staff Machine Learning Scientist - Core ml

Machine Learning
Model Development
Computer Vision
Representation Learning
Classification
Python
Data Engineering
MLOps
Statistical Rigor
Experiment Design
A/B Testing
Transformers
PyTorch
TensorFlow
Cloud Platforms (AWS, GCP, Azure)

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to the Staff Machine Learning Scientist role. Highlight your experience with machine learning models, Python skills, and any relevant projects that showcase your ability to solve complex problems in production settings.

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. Don’t forget to mention specific projects or experiences that relate to the responsibilities outlined in the job description.

Showcase Your Technical Skills: In your application, be sure to highlight your technical expertise, especially with frameworks like PyTorch or TensorFlow. Mention any experience you have with NLP, image classifiers, or cloud platforms, as these are key for the role.

Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!

How to prepare for a job interview at Depop

✨Know Your ML Stuff

Make sure you brush up on your machine learning concepts, especially those related to computer vision and classification. 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.

✨Showcase Your Leadership Skills

As a Staff Machine Learning Scientist, you'll need to demonstrate your ability to lead initiatives and mentor others. Prepare to share specific examples of how you've guided teams through complex projects and influenced decision-making across multi-functional groups.

✨Communicate Clearly

Practice explaining technical concepts in a way that non-technical stakeholders can understand. You might be asked to present your findings or ideas, so being able to communicate effectively is key. Think about how you can simplify complex topics without losing the essence.

✨Be Ready for Problem-Solving

Expect to tackle some ambiguous problems during the interview. Prepare for hypothetical scenarios where you’ll need to outline your approach to designing scalable ML solutions. Think about how you'd lead experiments and evaluate their outcomes to drive improvements.

Staff Machine Learning Scientist - Core ml
Depop

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