6 дней назад
MLOps Engineering Specialist (AWS)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
MLOps Engineering Specialist (AWS): Building and operating production-grade machine learning platforms with AWS SageMaker, covering data preparation, model deployment, monitoring, retraining, and governed lifecycle automation with an accent on scalable pipelines, security, and operational reliability. Focus on implementing drift detection, automated retraining, model promotion controls, observability, and secure real-time and serverless inference.
Location: Hybrid, with 3 days per week in the office and 2 days from home; Bristol or London, United Kingdom
Company
is a UK communications corporation operating brands including BT, EE, Openreach, and Plusnet.
What you will do
- Design and implement end-to-end MLOps workflows with AWS SageMaker Pipelines, Feature Store, Model Registry, and Experiments.
- Enable model promotion across development, test, pre-production, and production environments.
- Automate retraining based on data or model performance changes.
- Build lifecycle controls for versioning, testing, release governance, rollback, and environment promotion.
- Implement secure SageMaker workloads with least-privilege IAM roles and VPC network isolation.
- Develop model monitoring, drift detection, alerting, reporting, and scalable real-time or serverless inference solutions.
Requirements
- Strong hands-on experience with MLOps, CI/CD, code, data and model versioning, release governance, and production monitoring.
- Strong AWS experience, particularly with Amazon SageMaker deployment, monitoring, and drift or quality monitoring.
- Experience with observability for serverless systems, including logs, metrics, traces, distributed tracing, and dashboards.
- Experience with Docker and custom SageMaker containers.
- Experience with monitoring, alerting, incident response, and Infrastructure-as-Code using Terraform, CloudFormation, or CDK.
- Ability to work 3 days per week in a Bristol or London office.
Nice to have
- Experience with S3, ECR, IAM, Lambda, Step Functions, Glue, and VPC networking.
- Knowledge of data privacy, model governance, responsible AI, data lineage, and model explainability.
- Understanding of cost optimisation for training and inference workloads.
- AWS certification such as DevOps Engineer Professional, Machine Learning Engineer – Associate, or AI Practitioner.
Culture & Benefits
- Hybrid working arrangement with two home-working days per week.
- 10% on-target annual bonus.
- Private GP access, paid carers leave, and enhanced maternity, paternity, and adoption leave.
- Pension scheme with 5% employee and 10% employer contributions.
- Holiday purchase scheme and discounts on BT and EE products.
- Optional healthcare, dental, gym memberships, and other benefits.
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