Machine Learning Engineer (E-commerce)

TL;DR

Machine Learning Engineer (MLOps/E-commerce): Architecting and maintaining production-grade ML services for ranking, recommendations, and forecasting within a direct-to-consumer gifting platform with an accent on low-latency inference and scalable MLOps infrastructure. Focus on deploying resilient models, optimizing AWS-native platforms, and collaborating with data scientists to solve complex business problems.

Location: Hybrid in London

Company

hirify.global is the largest direct-to-consumer flower and gifting business in Europe and a certified B Corp.

What you will do

• Architect, implement, and maintain production-grade, low-latency ML services for ranking models, recommendation algorithms, and forecasting.
• Collaborate with data scientists and product managers to brainstorm and implement the best technical approaches for product and infrastructure problems.
• Design experiments to test hypotheses and evaluate improvements to existing models.
• Advise on data strategy to ensure the availability of datasets for future data science projects.
• Enhance the AWS-native MLOps platform to guarantee high availability and scalable inference.

Requirements

• Solid foundation in traditional ML techniques and the full model lifecycle, including handling class imbalance and hyperparameter tuning.
• Demonstrable experience designing, deploying, and monitoring ML services to solve business problems.
• Strong Python programming skills for delivering production-ready, well-structured, and documented code.
• Proficiency with SQL and experience working with large datasets.
• Ability to thrive in collaborative environments and work effectively with cross-functional teams.

Nice to have

• Experience working in e-commerce or a fast-growing consumer-facing startup.
• Experience working in a fully-remote setting.
• Exposure to Snowflake and dbt.

Culture & Benefits

• Flexible working arrangements, including the option to work from abroad.
• 25 days holiday plus your birthday and flexible bank holidays.
• Equity options available from the first day of employment.
• Enhanced family leave and a workplace nursery scheme.
• Flexible training framework for professional development at all career stages.
• ClassPass membership and discounts on company products.

Hiring process

• Initial 30-minute introductory chat with a Talent Acquisition Partner to discuss experience and motivations.