{"id":2120442,"url":"https://alion.io/job/depop-staff-machine-learning-scientist-core-ml","title":"Staff Machine Learning Scientist - Core ML","company":{"id":51473,"name":"Depop","domain":"depop.com","url":"https://alion.io/company/depop","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["London, United Kingdom"],"countries":["GB"],"hiring_countries":["GB"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":132000,"max_usd":256000,"period":"year","method":"role_seniority_country_cell","sample_n":23},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Computer Vision","optional":false},{"name":"Gemini","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"A/B Testing","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"GCP","optional":true},{"name":"NLP","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-10T00:00:00Z","employer_posted_date":"2026-09-10","last_verified_at":"2026-10-12T20:18:39Z","board_verified":true,"closed_at":null,"days_open":33,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":33},"description":"Company Description\nDepop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.\nFounded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life. We believe that everything you want already exists, and our role is to help people discover it.\nPowered by a team of over 500 people, our company is headquartered in London, with offices in New York. In 2021, Depop became a wholly-owned subsidiary of Etsy - the global marketplace for unique and creative goods - and continues to operate as a standalone company. For more information, visit www.depop.com\nWe aim 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.\nWe’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. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.\nAI Disclosure: We use AI tools (Google Gemini) to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters in identifying great talent but do not replace human decision-making. At Depop, every hiring decision is made by a human.\nIf, due to a disability, you need adjustments to complete the application, please let us know by sending an email with your name, the role to which you would like to apply, and the type of support you need to complete the application to .\nRole\nDepop 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.\nAs 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.\nResponsibilities\nYou will:\nOwn the design, development, and deployment of robust machine learning solutions to solve cross-cutting problems within the fashion resale space\n\nWork with and fine-tune models for representation learning, computer vision, and classification, and own efforts to productionize, scale, and evolve them as shared systems\n\nPartner 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\n\nLead 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\n\nStay 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\n\nParticipate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping, setting technical direction and improving for the team\n\nCommunicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making\n\nQualifications\nSkills and Experience\nProven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact\n\nDeep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow\n\nStrong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles\n\nAbility to lead the end-to-end lifecycle of ML initiatives, work independently in ambiguous problem spaces, and mentor and grow other scientists and engineers\n\nStrong collaboration and interpersonal skills, with experience aligning technical approaches with multi-functional teams and stakeholders\n\nA genuine curiosity about AI and a willingness to explore how it can enhance your day-to-day work\n\nBonus Points\nExperience with NLP, image classifiers, deep learning, or large language models\n\nExperience with experiment design and conducting A/B tests\n\nExperience building shared or platform-style ML systems\n\nExperience with Databricks and PySpark\n\nExperience working with AWS or another cloud platform (GCP/Azure)\n\nAdditional Information\nHealth + Mental Wellbeing\nPMI and cash plan healthcare access with Bupa\nSubsidised counselling and coaching with Self Space\nCycle to Work scheme with options from Evans or the Green Commute Initiative\nEmployee Assistance Programme (EAP) for 24/7 confidential support\nMental Health First Aiders across the business for support and signposting\n\nWork/Life Balance:\n25 days of annual leave with the option to carry over up to 5 days\nImpact hours: Up to 2 days of additional paid leave per year for volunteering\nFully 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.\nFlexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options *role-dependent\nAll offices are dog-friendly\nFamily Life:\nFor birth parent: 20 weeks of paid parental leave for full-time regular employees\nFor non-birth parents: 12 weeks of paid parental leave for full-time regular employees \nIVF leave, shared parental leave, and paid emergency parent/carer leave\nLearn + Grow:\nTwice-yearly development chats and yearly performance reviews\nLearning budget\nUpskilling our employees with company-wide training workshops, materials and resources\nYour Future:\nLife Insurance (financial compensation of 3x your salary)\nPension matching up to 6% of full base salary with Aviva\nDepop Extras:\nIn-office Depop Shop (that’s free!) and a packing station with free delivery.\nSpecial milestones are celebrated with gifts and rewards!","description_format":"text","description_chars":7012,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Annual leave","Flexible schedule","Life insurance","Parental 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