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Depop

The community-powered circular fashion marketplace. Shop what you love. Sell your clothes. Do it all over.

Staff Machine Learning Scientist – Core ML

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteLeadTeam 201-500H1B No SponsorCompany SiteLinkedIn

Location

United Kingdom

Posted

108 days ago

Salary

0

Seniority

Lead

Job Description

Staff Machine Learning Scientist – Core ML

Depop

• 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 difficulty and real-world applicability • Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and chip in 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 for the team • Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making

Job Requirements

  • 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
  • Experience with NLP, image classifiers, deep learning, or large language models (bonus)
  • Experience with experiment design and conducting A/B tests (bonus)
  • Experience building shared or platform-style ML systems (bonus)
  • Experience with Databricks and PySpark (bonus)
  • Experience working with AWS or another cloud platform (GCP/Azure) (bonus)

Benefits

  • 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
  • 25 days annual leave with option to carry over up to 5 days
  • 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
  • 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
  • 18 weeks of paid parental leave for full-time regular employees
  • IVF leave, shared parental leave, and paid emergency parent/carer leave
  • Budgets for conferences, learning subscriptions, and more
  • Mentorship and programmes to upskill employees
  • Life Insurance (financial compensation of 3x your salary)
  • Pension matching up to 6% of qualifying earnings
  • Employees enjoy free shipping on their Depop sales within the UK.
  • Special milestones are celebrated with gifts and rewards!

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