Applied Scientist: ML at Scale & Production Impact

ASOS.com Ltd; Camden Town; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Employee discount

Employee sample sales

Annual leave 25 days

Private medical care

Fixed annual payment

Learning opportunities

Job summary

ASOS.com Ltd in the United Kingdom is seeking an Applied Scientist to design, develop and deploy machine learning models that power decision-making and experiences across ASOS. You will work with data engineers, ML engineers, analysts and product managers to productionise models, evaluate impact and translate research into production systems that deliver measurable value.

You will join a team that uses Python and modern ML frameworks to tackle real-world business challenges, with opportunities

Qualifications

• Experience building and deploying ML models in production.
• Strong Python and ML framework experience (PyTorch, TensorFlow).
• Experience with large datasets and distributed processing.
• Ability to communicate complex ML concepts to non-technical stakeholders.

Responsibilities

• Design, develop and deploy machine learning models in production.
• Collaborate with engineers to productionise models and build scalable ML systems.
• Design experiments and evaluation frameworks to measure model performance and business impact.
• Partner with product and business stakeholders to create value with ML.

Skills

Python

ML frameworks

PyTorch

TensorFlow

Distributed data processing

MLOps

Data analysis

Communication

Tools

PyTorch

TensorFlow

Job description

ASOS.com Ltd in the United Kingdom is seeking an Applied Scientist to design, develop and deploy machine learning models that power decision-making and experiences across ASOS. You will work with data engineers, ML engineers, analysts and product managers to productionise models, evaluate impact and translate research into production systems that deliver measurable value.

You will join a team that uses Python and modern ML frameworks to tackle real-world business challenges, with opportunities