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- Tasks: Design and deploy machine learning systems, ensuring scalability and performance.
- Company: Join Broadridge, a leader in tech innovation with a focus on collaboration.
- Benefits: Enjoy a hybrid work model, competitive salary, and a supportive environment.
- Why this job: Make an impact in AI and ML while working with cutting-edge technologies.
- Qualifications: 5-8 years in cloud development, especially with AWS and automation tools.
- Other info: Be part of a diverse team that values flexibility and accountability.
The predicted salary is between 48000 - 84000 £ per year.
Responsibilities
- Design machine learning deployment, monitoring pipelines and engineering infrastructure to support enterprise ML systems at scale.
- Take offline models built by data scientists and turn them into production machine learning systems.
- Develop and deploy scalable tools and services to handle machine learning training and inference.
- Identify and evaluate new technologies to improve performance, maintainability, and reliability of client ML systems.
- Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
- Support model development with an emphasis on auditability, versioning, and data security.
- Facilitate the development and deployment of proof‑of‑concept machine learning systems.
- Communicate with clients to build requirements and track progress.
Qualifications & Skills
- 5‑8 years in cloud application development/administration with at least 4 years in AWS, Terraform, Jenkins, CloudFormation or similar IaC.
- Proven experience building end‑to‑end systems as a Platform Engineer, ML DevOps Engineer on AWS SageMaker and similar tools.
- Knowledge and experience with CI/CD tools, automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting, etc.).
- Strong hands‑on technical skills in automation, infrastructure as code, logging, monitoring and observability, infrastructure configuration, scripting languages and applications.
- Experience working in cloud ecosystem—building and deploying workloads on AWS.
- Associate certification (preferable) in AWS Development and/or Architect or any cloud related certification (Terraform/Chef).
- Understanding of AI, ML & Generative AI domain an added advantage.
- Ability to analyze escalations, prioritize, identify owners, track and facilitate blockers.
- Good understanding and knowledge of Chef / Python / Go and cloud networking.
- Essential security principles and processes.
- Excellent communication and interpersonal skills (verbal and written), ability to work effectively with a remote and multicultural team, following a collaborative and supportive approach.
- Strong analytical and organizational skills.
Hybrid work model. Broadridge is committed to fostering a collaborative, inclusive and healthy environment that promotes flexibility and accountability.
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Cloud DevOps Engineer (AWS) employer: NLP PEOPLE
Contact Detail:
NLP PEOPLE Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Cloud DevOps Engineer (AWS)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AWS, Terraform, and CI/CD. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common DevOps questions and scenarios. Practice explaining your past experiences with machine learning systems and how you've tackled challenges in cloud environments.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your relevant experience and passion for the role.
We think you need these skills to ace Cloud DevOps Engineer (AWS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, Terraform, and CI/CD tools. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool projects related to machine learning or cloud infrastructure, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at NLP PEOPLE
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS, Terraform, and CI/CD tools like Jenkins and Docker. Brush up on your hands-on skills with automation and infrastructure as code, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss specific challenges you've faced in previous roles, especially related to machine learning systems. Highlight how you identified issues, prioritised tasks, and facilitated solutions, as this demonstrates your analytical abilities.
✨Communicate Clearly and Effectively
Since the role involves client communication, practice articulating complex technical concepts in simple terms. This will show that you can bridge the gap between technical and non-technical stakeholders, which is crucial for success.
✨Demonstrate a Collaborative Mindset
Emphasise your experience working in diverse teams and your approach to collaboration. Share examples of how you’ve supported colleagues or contributed to a positive team environment, as this aligns with the company’s values.
