4 ΡΠ°ΡΠ° Π½Π°Π·Π°Π΄
Senior Applied Scientist (Machine Learning)
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Senior Applied Scientist (Machine Learning): Building scalable machine learning solutions that power business decisions, products, and customer experiences across an online fashion retailer with an accent on production deployment, model evaluation, and measurable business impact. Focus on researching emerging approaches, designing robust evaluation frameworks, writing production-quality code, and providing technical leadership across complex initiatives.
Location: HQ in London is mentioned; the work format and candidate location requirements are not specified.
Company
is an online fashion retailer building digital products and customer experiences for fashion customers worldwide.
What you will do
- Lead the design, development, and evaluation of machine learning solutions for complex business challenges.
- Identify opportunities where machine learning can create measurable business and customer value.
- Improve model performance, scalability, reliability, and operational impact across multiple use cases.
- Research and prototype emerging approaches from industry and academia, translating research into practical solutions.
- Design evaluation frameworks covering model quality, customer outcomes, and business impact.
- Partner with ML Engineers, Data Engineers, Analysts, Product Managers, and business stakeholders while mentoring other scientists.
Requirements
- Experience developing and deploying machine learning solutions in production environments.
- Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow, or similar technologies.
- Experience with large datasets and distributed data processing environments.
- Knowledge of testing, version control, and maintainable, reproducible software engineering practices.
- Experience across the end-to-end machine learning lifecycle, from problem definition and experimentation through deployment and monitoring.
- Ability to communicate complex technical concepts and provide technical leadership and mentoring.
Culture & Benefits
- Employee discount, employee sample sales, and a discretionary bonus scheme.
- 25 days of annual leave plus an additional celebration day.
- Private medical care and flexible benefits allowance.
- Matched pension contributions of up to 5%.
- Personalised learning and career development opportunities.
- Summer hours with 3pm finishes on Fridays during June, July, and August.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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