12 дней назад
Software Engineer (ML Enablement)
45 000 - 55 000GBP
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
Software Engineer (ML Enablement) (Python/AWS): Building tools, services, infrastructure, and pipelines that support scalable machine learning workflows across the BBC with an accent on cloud engineering, infrastructure as code, and reliable software delivery. Focus on designing maintainable ML enablement platforms, integrating data and machine learning pipelines, and solving monitoring, security, testing, and operational support challenges.
Location: Salford Dock House (primary), London Broadcasting House, or Glasgow Pacific Quay; hybrid attendance required one day a week.
Salary: £45,000–£55,000 per year, depending on relevant skills, knowledge, and experience.
Company
is a major media organisation with a Data Platforms department supporting technology and machine learning capabilities across the organisation.
What you will do
- Design, build, and maintain tools, services, and infrastructure for machine learning workflows.
- Develop and support data and machine learning pipelines and integrations.
- Apply TDD, CI/CD, clean design, testing, and code-quality practices.
- Contribute to architecture decisions, technical discussions, code reviews, reliability, and security.
- Collaborate with engineers, data scientists, and technical teams to define requirements and deliver solutions.
- Participate in pair programming and knowledge sharing.
Requirements
- Experience developing software with Python or a similar modern programming language.
- Understanding of software engineering principles, testing, version control, code quality, and CI/CD.
- Experience developing or supporting cloud-based services, preferably with AWS.
- Experience with infrastructure as code and automated delivery, such as AWS CDK or CloudFormation.
- Experience developing or maintaining data, software, or machine learning pipelines, including monitoring, reliability, security, and operational support.
- Eligibility to work in the United Kingdom is checked as part of employment screening.
Nice to have
- Experience with AWS services including SageMaker, S3, EC2, Lambda, IAM, VPC, KMS, or Bedrock.
- Experience with scalable architectures for data-driven products or services.
- Experience with MLOps, machine learning workflows, containerisation, or orchestration.
- Familiarity with machine learning concepts, statistical techniques, or machine learning frameworks.
Culture & Benefits
- Flexible 35-hour working week.
- 25 days of annual leave, with the option to buy up to five additional days.
- Defined pension scheme and discounted dental, healthcare, and gym benefits.
- Mentorship, learning opportunities, and professional development support.
- Inclusive, values-based working environment focused on collaboration, continuous learning, and craftsmanship.
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