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- Tasks: Lead the migration of ML workloads to AWS SageMaker and ensure operational reliability.
- Company: Join a supportive tech company with a flexible working culture.
- Benefits: Enjoy remote work options and a collaborative environment.
- Other info: Great opportunity for career growth in a dynamic field.
- Why this job: Be a technical leader and make a significant impact in ML operations.
- Qualifications: Proven experience with Python-based ML workloads and strong leadership skills.
The predicted salary is between 70000 - 90000 £ per year.
CreateFuture is seeking a Lead MLOps Engineer in the UK to take technical leadership in migrating ML workloads from Databricks to AWS SageMaker. This role requires proven hands-on experience and strong knowledge of Python-based ML workloads. You will act as the technical authority for architectural decisions, ensuring operational reliability and stability. The company offers a supportive culture and flexible working arrangements, including hybrid and remote options.
Lead MLOps Engineer (Remote) — SageMaker Migrations in Manchester employer: CreateFuture
Contact Detail:
CreateFuture Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead MLOps Engineer (Remote) — SageMaker Migrations in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the MLOps community, especially those who have experience with AWS SageMaker. Join relevant online forums or LinkedIn groups to connect and learn from others.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python-based ML projects, especially any migrations you've done. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of MLOps best practices and AWS services. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Lead MLOps Engineer (Remote) — SageMaker Migrations in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python-based ML workloads and any previous migrations you've led. We want to see how your skills align with the role, so don’t be shy about showcasing your 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 the Lead MLOps Engineer position. Share your passion for AWS SageMaker and how you can contribute to our supportive culture.
Showcase Your Technical Leadership: In your application, emphasise your experience in making architectural decisions and ensuring operational reliability. We’re looking for someone who can take charge, so let us know how you've done this in the past!
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 us during the process!
How to prepare for a job interview at CreateFuture
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and any relevant MLOps tools, especially AWS SageMaker. Be ready to discuss your hands-on experience with migrating ML workloads and how you've tackled challenges in the past.
✨Showcase Your Leadership Skills
As a Lead MLOps Engineer, you'll need to demonstrate your ability to lead technical discussions and make architectural decisions. Prepare examples of how you've successfully led projects or teams, focusing on your decision-making process and the outcomes.
✨Understand Their Culture
CreateFuture values a supportive culture, so be prepared to discuss how you can contribute to that environment. Think about how you can foster collaboration and support within a remote or hybrid team setting.
✨Ask Insightful Questions
Prepare thoughtful questions about their current ML workloads and the challenges they face with Databricks to AWS SageMaker migrations. This shows your genuine interest in the role and helps you assess if it's the right fit for you.