Machine Learning Scientist

DEPOP; London; Hybrid; GBP 45,000 - 75,000; Full time

Job summary

Join a forward-thinking company as a Machine Learning Scientist, where you'll leverage cutting-edge technology to enhance the selling experience in the fashion resale industry. Collaborate with a diverse team to create innovative machine learning models, utilizing your expertise in NLP, computer vision, and data engineering. This role not only offers the chance to work on exciting projects but also provides a supportive environment that values work-life balance and continuous learning. With flexible working options and a focus on employee wellbeing, this is an opportunity to make a significant impact while growing your career in a dynamic field.

Benefits

Private Medical Insurance

Cycle to Work scheme

25 days annual leave

Flexible working options

Paid parental leave

Learning and development budgets

Life Insurance

Employee Assistance Programme

Free shipping on Depop sales

Celebration gifts and rewards

Qualifications

• Proven experience as a Machine Learning Scientist delivering models for industry-scale challenges.
• Strong knowledge of ML frameworks like PyTorch and TensorFlow, alongside Python proficiency.

Responsibilities

• Design and deliver machine learning solutions for the fashion resale market.
• Conduct experiments and present findings to both technical and non-technical audiences.

Skills

Machine Learning

Natural Language Processing (NLP)

Computer Vision

Python

Data Engineering

MLOps

Collaboration

Experiment Design

Education

Bachelor's Degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Transformers

Databricks

PySpark

AWS

Job description

The Role

Depop is looking for a dedicated Machine Learning Scientist to join our Ranking team in the UK. You will work alongside a cross-functional team of Product Managers, Designers, Backend & Frontend Engineers, and other Data Scientists playing a key role in building innovative machine learning models to power Depop's selling experience.

Responsibilities:

• Research, design, and deliver machine learning solutions to solve problems within the fashion resale space.
• Work with and fine-tune (multimodal) large language models; textual understanding using natural language processing algorithms / image feature extraction using computer vision models.
• Understand requirements from various stakeholders across the business, designing machine learning solutions to solve business problems, such as: How can we capitalize on recent advances in generative AI to make the selling process as easy as possible, and how can we extract information from image and text inputs to generate rich features used in our recommender and search engines?
• Set up and conduct large-scale experiments to test hypotheses and drive product development.
• Keep up to date with research, contribute to Machine Learning groups, and apply new techniques for (multimodal) LLMs, NLP, computer vision, etc.
• Participate in team ceremonies (follow the agile cadence, technical whiteboarding sessions, product road mapping, etc.).
• Report and present technical findings to technical and non-technical audiences.

Requirements:

• Experience working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problems.
• Solid understanding of machine learning concepts, familiarity working with frameworks such as Transformers, PyTorch, or TensorFlow.
• Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps.
• Collaborative and humble team player with the ability to work with cross-functional teams, including technical and non-technical stakeholders.
• Passion for learning new skills and staying up-to-date with ML algorithms.

Bonus:

• Experience working with NLP, Image classifiers, and Transformers.
• Experience with deep learning & large language models.
• Experience with experiment design and conducting A/B tests.
• Experience with Databricks and PySpark.
• Experience working with AWS or another cloud platform (GCP/Azure).

Additional information

Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa; subsidized 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.

Work/Life Balance: 25 days annual leave with the option to carry over up to 5 days; 1 company-wide day off per quarter; Impact hours: 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.

Flexible Working: 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.

Family Life: 18 weeks of paid parental leave for full-time regular employees; IVF leave, shared parental leave, and paid emergency parent/carer leave.

Learn + Grow: Budgets for conferences, learning subscriptions, and more; mentorship and programmes to upskill employees.

Your Future: Life Insurance (financial compensation of 3x your salary); pension matching up to 6% of qualifying earnings.

Depop Extras: Employees enjoy free shipping on their Depop sales within the UK; special milestones are celebrated with gifts and rewards!