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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 machine learning models.
- Qualifications: Experience with AWS SageMaker and CI/CD pipelines is essential.
- Other info: Short-term contract with opportunities for growth in a collaborative setting.
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
Locations
Platform Engineer SageMaker - SC Cleared in Newcastle upon Tyne, North East 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, North East
✨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. This can really set you apart from the crowd and 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 recommend doing mock interviews with friends or using online platforms to get comfortable with the questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly can sometimes give you an edge over other candidates. Let’s get you that contract!
We think you need these skills to ace Platform Engineer SageMaker - SC Cleared in Newcastle upon Tyne, North East
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 role, 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. Mention your hands-on experience and how you can hit the ground running in a fast-paced environment.
Showcase Your Technical Skills: Be specific about your technical expertise, especially with CI/CD pipelines and Python. We love seeing concrete examples of how you've used these skills in previous roles, so don’t hold back!
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 the role. Plus, it’s super easy!
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 and maintained MLOps pipelines, as well as any challenges you faced and how you overcame them.
✨Showcase Your MLOps Best Practices
Prepare to talk about MLOps best practices you've implemented in previous roles. Highlight your experience with CI/CD pipelines for ML workloads and how you've automated model training and deployment workflows.
✨Collaborate Like a Pro
Since collaboration is key in this role, think of examples where you've worked closely with data scientists and engineering teams. Be ready to explain how you contributed to productionising models and ensuring their scalability and reliability.
✨Security Clearance Matters
With SC clearance being a requirement, be prepared to discuss your experience with security protocols in cloud environments. Make sure you can articulate how you've ensured the security of ML systems in your past work.
