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For Companies At a Glance
- Tasks: Design and maintain MLOps pipelines using AWS SageMaker in a fast-paced environment.
- Company: Join a dynamic team focused on machine learning innovation.
- Benefits: Competitive daily rate, remote work, and the chance to enhance your skills.
- Why this job: Make an impact by deploying cutting-edge ML models and collaborating with experts.
- Qualifications: Experience with AWS SageMaker, Python, and CI/CD for ML workloads required.
- Other info: Short-term contract with potential for future opportunities.
We are seeking an experienced MLOps Engineer with strong expertise in AWS SageMaker to support the delivery, deployment, and operationalisation of machine learning models. This is a short-term contract role, ideal for someone who can hit the ground running in a fast-paced environment.
Key Responsibilities
- Design, build, and maintain MLOps pipelines using AWS SageMaker
- Deploy, monitor, and manage machine learning models in production
- Automate model training, testing, and deployment workflows
- Ensure scalability, reliability, and security of ML systems
- Collaborate with data scientists and engineering teams to productionise models
- Troubleshoot and optimise existing ML pipelines
Required Skills & Experience
- Strong hands-on experience with AWS SageMaker
- Solid understanding of MLOps best practices
- Experience with CI/CD pipelines for ML workloads
- Proficiency with Python and relevant ML frameworks
- Experience working in cloud-based environments (AWS)
Security Requirements
- Active SC Clearance
Platform Engineer SageMaker - SC Cleared in Newcastle upon Tyne employer: Brightbox GRP Ltd
Contact Detail:
Brightbox GRP Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Platform Engineer SageMaker - SC Cleared in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to your connections in the MLOps and AWS communities. Attend meetups or webinars, and don’t be shy about asking for referrals. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving AWS SageMaker. We recommend including links to GitHub repos or any live demos. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common MLOps scenarios and AWS SageMaker functionalities. We suggest doing mock interviews with friends or using online platforms. The more comfortable you are, the better you’ll perform!
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly can sometimes give you an edge over others. Don’t miss out on your dream role!
We think you need these skills to ace Platform Engineer SageMaker - SC Cleared in Newcastle upon Tyne
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS SageMaker and MLOps. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. We love seeing enthusiasm and a clear understanding of the responsibilities outlined in the job description.
Showcase Your Technical Skills: Since this role requires strong technical expertise, make sure to mention your proficiency with Python and any relevant ML frameworks. We’re looking for candidates who can hit the ground running, so highlight your hands-on experience!
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’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Brightbox GRP Ltd
✨Know Your AWS SageMaker Inside Out
Make sure you brush up on your AWS SageMaker knowledge before the interview. Be ready to discuss specific projects where you've designed, built, or maintained MLOps pipelines. Highlight your hands-on experience and any challenges you faced while deploying machine learning models.
✨Showcase Your MLOps Best Practices
Prepare to talk about MLOps best practices you've implemented in previous roles. Discuss how you've automated model training, testing, and deployment workflows, and be ready to share examples of how you ensured scalability and reliability in your ML systems.
✨Demonstrate Your CI/CD Pipeline Experience
Since this role requires proficiency with CI/CD pipelines for ML workloads, come equipped with examples of how you've set these up in the past. Be specific about the tools you used and the impact they had on your team's efficiency and productivity.
✨Collaborate and Communicate Effectively
As collaboration is key in this role, think of instances where you've worked closely with data scientists and engineering teams. Be prepared to discuss how you communicated technical concepts to non-technical stakeholders and how you tackled any conflicts that arose during projects.
