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Senior Machine Learning Engineer (MLOps)
ASOS
London, GBR
Full-time
Senior
Hybrid
Discovered 4 days ago
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Key Skills for This Role
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Full Job Posting
BeneFITS’
- Employee discount (hello ASOS discount!)
- Employee sample sales
- 25 days paid annual leave + an extra celebration day for a special moment
- Discretionary bonus scheme
- Private medical care scheme
- Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
- Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role
- We’re ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.
- But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.
- Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.
Qualifications
- Strong software engineering fundamentals with experience designing and building production systems at scale.
- Experience developing distributed systems, microservices or high-throughput backend platforms.
- Strong programming skills in Python, Java, Kotlin, Go, Scala or similar languages.
- Experience building and operating services in AWS, Azure or GCP environments.
- Hands-on experience with Kubernetes, containerisation and cloud-native technologies.
- Experience implementing CI/CD pipelines and automated deployment processes.
- Knowledge of Infrastructure-as-Code tools such as Terraform, Pulumi or CloudFormation.
- Experience with monitoring, alerting and observability tooling.
- Experience building reliable, resilient and scalable systems with a focus on performance and operational excellence.
- Experience working with data-intensive systems, streaming technologies or large-scale distributed processing platforms.
- Exposure to machine learning systems, model serving, feature stores, training infrastructure or MLOps practices.
- Experience supporting recommendation systems, search platforms, personalisation engines or other customer-facing data products is advantageous.
- Comfortable providing technical leadership, mentoring engineers and influencing architectural direction.
- Strong collaboration and communication skills, with experience working in cross-functional product teams.
- Experience supporting large-scale model training and inference workloads.
- Knowledge of vector search, ranking systems, retrieval architectures or recommendation platforms.
- Exposure to LLMs, Generative AI and production AI systems.
- Experience building internal developer platforms, engineering enablement tooling or shared capabilities used across multiple teams.
About ASOS
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