Machine Learning Engineer
Inara
- London, England, United Kingdom
- London, England, United Kingdom
Über
Duration:
Initially 3 months Workplace:
Remote, with occasional travel to client-site Inara are supporting a consultancy-led team delivering
production-grade machine learning platforms
for a range of end clients, and they’re looking for a
senior, hands-on Contract MLOps Engineer
to help take ML systems from experimentation into reliable, scalable production. This role is firmly focused on
ML enablement and platform engineering
rather than model research. You’ll be the person ensuring models can be trained, tracked, deployed, governed, and monitored properly in real-world environments. What you’ll be doing
Designing and building
end-to-end MLOps platforms
that support the full ML lifecycle Implementing and operating
MLflow
for experiment tracking, model registry, and versioning Enabling
production deployments
of ML models (batch and/or real-time) Putting robust
CI/CD pipelines
in place for ML workflows Partnering closely with Data Scientists to move models from notebooks into production Establishing best practices around
model governance, monitoring, retraining, and environments Integrating ML platforms with
Databricks
and cloud-native services What we’re looking for
Strong,
real-world MLOps experience
(this is not a theoretical role) Deep hands-on MLflow experience
— this is essential Proven track record of
productionising ML models
across multiple client or project environments Background in one or more of: DevOps with ML platforms Data Science with a strong production focus Experience designing, supporting, and operating
ML systems in production Technical environment (experience expected across most of these)
MLflow (expert-level) Databricks Cloud platforms
(AWS preferred; SageMaker exposure a bonus) CI/CD for ML workloads Docker and Kubernetes Infrastructure as Code
(Terraform or similar)
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Sprachkenntnisse
- English
Hinweis für Nutzer
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