Senior Machine Learning Scientist
Depop
full-time
Posted on:
Location Type: Hybrid
Location: London • United Kingdom
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Job Level
About the role
- Research, design, and deliver machine learning solutions to detect fraud, abuse, and policy violations in user-generated content
- Work closely with Trust, Product, Policy, and Engineering partners to translate business and safety requirements into effective ML systems
- Build, train, and evaluate LLM-based models for text and multimodal classification, detection, and reasoning tasks
- Set up and run large-scale offline experiments and online evaluations to test hypotheses and measure impact
- Stay up to date with state-of-the-art research in large language models and modern deep learning, applying new techniques where appropriate
- Participate in team ceremonies including agile rituals, technical design discussions, and roadmap planning
- Clearly communicate technical approaches, results, and trade-offs to both technical and non-technical stakeholders
Requirements
- Experience working as a Machine Learning Scientist, with a track record of delivering models to solve real-world, production-scale problems
- Strong understanding of machine learning fundamentals, with hands-on experience using frameworks such as PyTorch and modern architectures (e.g. Transformers, large language models)
- Proficiency in Python, with the ability to write production-quality code and a solid understanding of data pipelines, model training, and MLOps practices
- Comfortable working with noisy, weakly-labeled, or imbalanced data typical of trust and safety domains
- Collaborative, pragmatic, and curious team player, able to work effectively with cross-functional partners
- Passion for learning, experimentation, and staying current with advances in machine learning
- Bonus points
- Experience building classification or scoring models for trust, safety, fraud, abuse, or policy enforcement use cases
- Hands-on experience fine-tuning, evaluating, or deploying large language models for real-world applications
- Experience with experiment design, offline evaluation, and online testing (e.g. A/B tests)
- Experience working with Databricks and PySpark
- Experience deploying ML systems on AWS or other cloud platforms (GCP/Azure)
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, to give you a chance to recharge or do something you love.
- 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!
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learninglarge language modelsdeep learningPyTorchPythonMLOpsdata pipelinesclassification modelsexperiment designA/B testing
Soft Skills
collaborativepragmaticcuriousteam playercommunication