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- Tasks: Review and refine AI outputs, ensuring accurate MLOps reasoning and practical deployment procedures.
- Company: Join a leading AI lab connecting expert freelancers with innovative projects.
- Benefits: Flexible remote work, access to AI Academy, and opportunities for collaboration.
- Other info: Work 8-20 hours per week in a dynamic, high-impact environment.
- Why this job: Make a real impact on AI infrastructure while working flexibly around your schedule.
- Qualifications: Senior-level MLOps experience and ability to provide critical feedback.
The predicted salary is between 40 - 60 £ per hour.
Freelance | 8–20 hrs/week | Remote (EU/UK)
Are you an experienced MLOps engineer who instinctively spots gaps in technical reasoning and understands the complex realities of machine learning operations? Do you have 8 to 20 hours per week available alongside your main job or consulting projects? Join us in shaping how AI understands and applies MLOps expertise at scale.
About the Role
10x.team connects expert freelancers with leading AI labs building next-generation models. We are looking for knowledgeable MLOps engineers based in the EU or UK to enhance the accuracy, depth, and real-world relevance of AI-powered machine learning infrastructure.
What You Will Do
- Review and refine AI-generated outputs related to machine learning operations, deployment pipelines, monitoring, and practical aspects of MLOps
- Evaluate AI responses for technical accuracy, operational reliability, and compliance with real-world requirements
- Draft realistic MLOps scenarios based on your direct professional experience
- Create scenario variations from different perspectives (e.g. MLOps engineer, data scientist, developer, or product owner)
- Identify gaps, oversights, or weak reasoning in AI-generated MLOps content
In simple terms: You will assess and improve AI-generated content, ensuring it reflects true MLOps reasoning, authentic documentation, and practical deployment procedures. Rather than conducting traditional MLOps projects, you’ll apply your expertise to help AI systems understand and reason about MLOps at scale.
Who You Are
- A senior-level MLOps engineer with significant professional experience within the EU or UK
- Experienced in designing, building, and operating machine learning pipelines and infrastructure
- Skilled at evaluating deployment strategies, automation, and compliance with operational standards
- Comfortable working independently and providing structured, critical feedback
- Available for 8–20 hours per week, with prompt availability
Why Join?
- Flexible, fully remote freelance work that fits your current commitments
- Apply your MLOps expertise in a rapidly evolving, high-impact AI environment
- Directly contribute to building advanced AI-powered infrastructure and operational systems
- Free access to our in-house AI Academy to further develop your AI skillset
- Clear onboarding, structured tasks, and ongoing opportunities for collaboration
How to apply
To complete your application, you’ll receive an email right after applying with a link to:
- A short written evaluation
- A brief AI-powered interview
- A quick compliance check (credentials & identity)
Important: Your application is only complete once you finish these steps via the link in the email. After successful onboarding, you’ll be eligible to start on upcoming projects as they become available. Join us to help shape the MLOps expertise of the world’s most advanced AI models!
ML Ops Engineer - AI Trainer - Freelance - 8-20hrs/week in London employer: 10x.Team
Contact Detail:
10x.Team Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Ops Engineer - AI Trainer - Freelance - 8-20hrs/week in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the MLOps field and let them know you're on the lookout for freelance gigs. You never know who might have a lead or can refer you to someone looking for your expertise.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past MLOps projects and any relevant AI work. This will give potential clients a taste of what you can do and help you stand out from the crowd.
✨Tip Number 3
Stay active in online communities! Join forums, LinkedIn groups, or Discord channels focused on MLOps and AI. Engaging with others in the field can lead to job opportunities and collaborations that you might not find elsewhere.
✨Tip Number 4
Apply through our website! We’ve got some fantastic freelance opportunities waiting for you. Make sure to complete all application steps, including the evaluation and interview, to increase your chances of landing that perfect role.
We think you need these skills to ace ML Ops Engineer - AI Trainer - Freelance - 8-20hrs/week in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your application to highlight your MLOps experience. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects and achievements!
Be Clear and Concise: When filling out your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your expertise and how you can contribute to our team.
Showcase Your Problem-Solving Skills: Since the role involves identifying gaps in AI outputs, share examples of how you've tackled similar challenges in the past. We love seeing your critical thinking in action!
Complete All Steps: After applying, check your email for the next steps. It’s super important to finish the written evaluation and interview to complete your application. We’re excited to see you join us!
How to prepare for a job interview at 10x.Team
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps knowledge before the interview. Familiarise yourself with the latest trends, tools, and best practices in machine learning operations. Being able to discuss these confidently will show that you're not just experienced but also passionate about the field.
✨Prepare Real-World Scenarios
Since the role involves evaluating AI-generated outputs, think of specific scenarios from your past experience that highlight your skills. Be ready to discuss how you've tackled challenges in MLOps, as this will demonstrate your practical understanding and ability to apply your knowledge effectively.
✨Practice Critical Feedback
The job requires providing structured, critical feedback on AI outputs. Prepare examples of how you've given constructive criticism in previous roles. This will help you articulate your thought process during the interview and show that you can evaluate technical accuracy and operational reliability.
✨Show Your Flexibility
As this is a freelance position with flexible hours, be prepared to discuss how you manage your time effectively. Highlight your ability to balance multiple commitments while delivering high-quality work. This will reassure them that you can meet the demands of the role without compromising on quality.