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- Tasks: Architect and support AI solutions, enhancing machine learning capabilities across the organisation.
- Company: Join Broadridge, a company that empowers others and fosters innovation.
- Benefits: Hybrid work model, competitive salary, and a culture of continuous learning.
- Why this job: Be at the forefront of AI and machine learning, making a real impact.
- Qualifications: 5-8 years in cloud development, with strong AWS and DevOps skills.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
At Broadridge, we have built a culture where the highest goal is to empower others to accomplish more. If you are passionate about developing your career while helping others along the way, come join the Broadridge team.
We are excited to announce an opportunity for AWS Cloud DevOps Engineer to join our organization as part of our AI Enablement Team. In this role, you will play a crucial role in architecting, deploying and supporting the solutions that enhance our AI capabilities across the organization, with a specific focus on GenAI projects. You will be driving innovation and delivering cutting-edge solutions. Your expertise will contribute to the development of our platform, shaping its capabilities and providing impactful solutions.
Join our dynamic team and be part of a collaborative environment that fosters continuous learning and creativity. If you are passionate about machine learning, AI, and want to contribute to the platform capability development for our whole organization, we invite you to apply.
Responsibilities:- Design the ML deploy, monitoring pipelines and engineering infrastructure to support enterprise machine learning systems at scale.
- Take offline models data scientists build and turn them into a real machine learning production system.
- 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 our clients' machine learning 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.
- Overall 5-8 years in cloud application development/administration with at least 4 years of experience in AWS, Terraform, Jenkins, CloudFormation or any other IAAC.
- 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.
- Strong hands-on technical skills in automation (Jenkins, GitLab, Docker, Kubernetes, Shell Scripting, etc.).
- Experience working in Cloud ecosystem - building and deploying workloads on cloud, preferably AWS.
- Associate Certification (preferable) in AWS Development and/or Architect or any cloud-related certification (Terraform/Chef).
- Understanding of AI, ML & Generative AI domain will be 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.
- Strong analytical and organizational skills - ability to understand the design documents and communicate implementations.
This role is considered hybrid. We are dedicated to fostering a collaborative, engaging, and inclusive environment and are committed to providing a workplace that empowers associates to be authentic and bring their best to work.
Cloud DevOps Engineer (AWS) in London employer: Broadridge Trading & Connectivity Solutions
Contact Detail:
Broadridge Trading & Connectivity Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Cloud DevOps Engineer (AWS) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already at Broadridge. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you’ve got a GitHub or portfolio showcasing your projects, make sure to share it during interviews. It’s a great way to demonstrate your hands-on experience with AWS and DevOps tools.
✨Tip Number 3
Prepare for technical questions! Brush up on your knowledge of CI/CD, Terraform, and machine learning concepts. Being able to discuss these topics confidently will set you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Broadridge team.
We think you need these skills to ace Cloud DevOps Engineer (AWS) in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Cloud DevOps Engineer role. Highlight your experience with AWS, Terraform, and CI/CD tools, as these are key to what we're looking for!
Showcase Your Projects: Don’t just list your skills; give us examples of projects where you've applied them. If you've built end-to-end systems or worked on machine learning projects, let us know how you contributed!
Be Honest and Transparent: Remember, honesty is crucial in our hiring process. Be upfront about your skills and experiences. We value authenticity and want to see the real you in your application.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows your enthusiasm for joining our team!
How to prepare for a job interview at Broadridge Trading & Connectivity Solutions
✨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 knowledge of machine learning concepts and how they apply to cloud infrastructure. Being able to discuss specific projects or experiences where you've implemented these technologies will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in previous roles, especially those related to deploying and maintaining machine learning systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it clear how your contributions led to successful outcomes.
✨Communicate Clearly and Collaboratively
Since this role involves working with a diverse team, practice articulating your thoughts clearly. Be ready to explain complex technical concepts in simple terms, as you may need to communicate with non-technical stakeholders. Highlight any experience you have in collaborative environments.
✨Prepare Questions for Them
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, the company culture, and how they envision the role evolving. This shows your genuine interest in the position and helps you assess if it’s the right fit for you.
