At a Glance
- Tasks: Enhance AI models and optimise machine learning workflows on your own schedule.
- Company: Join 10x Team, connecting freelancers with leading AI labs.
- Benefits: Flexible freelance work, remote opportunities, and free access to AI Academy.
- Other info: Work 8-20 hours per week with structured onboarding and collaborative projects.
- Why this job: Shape the future of AI and make a real impact in ML operations.
- Qualifications: Experience in MLOps and strong feedback skills required.
The predicted salary is between 30 - 50 £ per hour.
Are you a machine learning and operations expert interested in shaping the future of artificial intelligence? Do you want to use your expertise to help train smarter AI models—on your own terms and schedule? Join 10x Team as a Freelance Machine Learning Operations Engineer – AI Trainer and contribute to building next-generation AI in real-world operations and ML workflows.
About Us
10x Team connects freelance professionals with leading AI labs to develop advanced AI models. We are seeking experienced machine learning operations (MLOps) specialists based in the EU or UK to ensure AI-generated workflows, deployment processes, and decision-making are accurate, relevant, and grounded in industry best practices.
Key Responsibilities
- Review and enhance AI-generated content on machine learning operations, model deployment, and workflow optimization.
- Assess the accuracy, technical relevance, and real-world viability of AI-driven ML operations scenarios and recommendations.
- Develop example use cases, deployment strategies, and risk management exercises based on your ML industry experience.
- Create multiple scenario variations reflecting perspectives of various ML operations roles, from engineers to stakeholders.
- Identify gaps or flawed assumptions in AI outputs and provide clear, actionable feedback.
About You
- Experienced MLOps engineer or manager with a strong background in deploying, optimizing, and overseeing machine learning systems.
- Based in the EU or UK.
- Demonstrated expertise in implementing and reviewing ML operations strategies, workflow automation, and operational excellence in machine learning.
- Highly organized and skilled at providing direct, constructive feedback.
- Available 8–20 hours per week and reliable in communications.
Why Join 10x Team
- Flexible, project-based freelance work—100% remote.
- Use your machine learning operations expertise to help build better AI.
- Make a direct impact by shaping the AI’s understanding of complex ML workflows and deployment challenges.
- Free access to our AI Academy for professional upskilling.
- Structured onboarding, clear project briefs, and ongoing collaborative opportunities.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote in London
✨Showcase Your Skills with a Public Portfolio
As a freelancer in data science, having a killer portfolio is essential. Showcase your projects on platforms like GitHub or create a personal website that details your work and techniques. This gives potential clients a clear picture of what you can do and helps you stand out from the competition.
✨Get Involved in Data Science Communities
Tap into online forums like Kaggle or Stack Overflow. Not only can you showcase your expertise, but you can also connect with other data scientists and potential clients. Plus, participating in competitions and discussions can elevate your profile in the field.
✨Leverage Local Networking Opportunities
Keep an eye out for local data science meetups or tech events in your area. These are golden opportunities to meet potential clients and collaborators face-to-face. Plus, who doesn't love a bit of networking over pizza and drinks?
✨Pitch Your Services Directly to Companies
Don't just wait for freelancing platforms to bring clients to you—be proactive! Research companies that could benefit from data science services and craft tailored pitches. Mention specific pain points you can address for them. Let’s get that freelance hustle going!
We think you need these skills to ace Machine Learning Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote in London
Some tips for your application 🫡
Showcase Your Projects:When applying for a freelance data science role like Machine Learning Operations Engineer - AI Trainer - Freelance - 8-20hrs/week - Remote at 10x.Team, it’s crucial to highlight your projects. Include a portfolio that features at least two or three projects involving data analysis, machine learning, or visualisation. Make sure to describe the tools and methodologies you used, so we can see your skills in action!
Quantify Your Achievements:Freelance gigs, especially in data science, often ask for proven results. In your CV, include any relevant metrics or outcomes from your previous work. Did your analysis help reduce costs by a certain percentage? Or did your predictive model improve performance? Numbers speak volumes!
Introduce Your Style:Since freelancing is all about your individual style and approach, use your cover letter to share how you tackle data problems. This is your chance to let us know how you think, your creative problem-solving methods, and how you would approach a project at 10x.Team.
Be Real About Your Rates:When you send in your application, don’t forget to mention your freelance rates and availability. We appreciate clarity up front, and it helps us gauge if you fit within our budget and timeline. Being transparent in this aspect shows professionalism and readiness!
How to prepare for a job interview at 10x.Team
✨Show Off Your Data Wizardry
As a freelancer in data science, you'll want to present a portfolio that showcases your best projects. We should pull together examples where you tackled real problems with data analytics, machine learning models, or visualisations. It's all about demonstrating your skills in action!
✨Be Ready to Dive Deep into Technical Questions
Expect to encounter some technical grilling during the interview. Prepare to discuss statistical methods, algorithms, or maybe even tackle a live coding challenge. We should brush up on tools like Python, R, or SQL—those are key players in the data science field. Don't just know them; be ready to explain your thought process!
✨Help Them Understand Your Work Style
Freelance gigs often mean you'll be working independently, so we need to convey our self-motivation and time management skills. Be prepared to talk about how you’ve handled multiple projects or met tight deadlines before. Sharing your approach to client communication can also give them confidence in your ability to deliver remotely.
✨Pitch Your Value Proposition
When freelancing, it’s crucial to clearly articulate what makes you unique. We should highlight not just technical skills but also the business impact of our projects. Think of a couple of stories where your data insights drove decision-making—this can be a game changer in showing why they should choose you for their freelance needs!
