Senior Machine Learning Scientist - Recommendations

Job Description

Depop is looking for a versatile Senior Machine Learning Scientist to join our Recommendations team in the UK. As part of the team, you will work alongside a Product Manager, Backend Engineers, and other ML Scientists, playing a key role in building innovative models to power Depop's search engine and ranking across the app.

Responsibilities:

• Research, design, and deliver ML solutions to address problems within the search & discovery space, including:
  • Learning-to-rank models
  • Vector search & embedding models
  • etc.
• Understand requirements from various partners across the business, designing machine learning solutions to solve problems such as:
  • How can we surface relevant results for this search?
  • How can we show users personalized results in real time?
  • What is the right price for this user?
• Set up and conduct large-scale experiments to test hypotheses and drive product development.
• Keep up to date with pioneering research, contribute to Machine Learning groups, and apply new techniques for NLP, image processing, etc.
• Participate in team ceremonies (follow the agile cadence, technical whiteboarding sessions, product road mapping, etc.)

Qualifications:

Significant experience (3+ years) working as a Machine Learning Scientist, with a proven track record of delivering models to solve industry-scale problems.

• Experience with experiment design and conducting A/B tests.
• Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps.
• Solid understanding of machine learning concepts, familiarity with frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Collaborative and humble team player capable of working with cross-functional teams, including technical and non-technical stakeholders.
• Passion for learning new skills and staying up-to-date with ML algorithms.

Bonus points:

• Experience with Databricks and PySpark.
• Experience with deep learning & large language models.
• Experience with traditional, semantic, and hybrid search frameworks (e.g., Elasticsearch).
• Experience working with AWS or other cloud platforms (GCP/Azure).

Additional information:

Health & Mental Wellbeing: PMI and cash plan healthcare access with Bupa, subsidized counseling and coaching, Cycle to Work scheme, Employee Assistance Programme (EAP), Mental Health First Aiders.

Work/Life Balance: 25 days annual leave, option to carry over 5 days, quarterly company-wide day off, impact hours for volunteering, fully paid 4-week sabbatical after 5 years.

Flexible Working: Hybrid model with Flex, Office Based, and Remote options, dog-friendly offices, ability to work abroad for 4 weeks/year in UK tax treaty countries.

Family Life: 18 weeks paid parental leave, IVF leave, shared parental leave, emergency parent/carer leave.

Learn & Grow: budgets for conferences and subscriptions, mentorship programs.

Your Future: Life Insurance (3x salary), pension matching up to 6%, employee perks like free UK shipping on Depop sales, celebration gifts and rewards.

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