At a Glance
- Tasks: Shape the future of AI by training advanced generative systems and optimising workflows.
- Company: Outlier, a leader in AI innovation with a focus on collaboration.
- Benefits: Remote work options, competitive salary, and opportunities for professional growth.
- Other info: Dynamic remote environment with exciting projects and career advancement potential.
- Why this job: Join a cutting-edge team and make a real impact in AI technology.
- Qualifications: 2+ years in backend engineering or AI automation, strong coding skills required.
The predicted salary is between 50000 - 60000 € per year.
About the Project
Outlier helps the world's most innovative companies improve their AI agents by providing human feedback. We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents. Our projects focus on teaching these systems how to design, coordinate, and optimize complex, real-world architectural workflows.
Whether you are a passionate orchestration guru or experienced software developer — we want you to help us train the world's most advanced generative systems.
Ideal Qualifications
- 2+ years of experience in backend engineering, AI automation, or complex systems integration.
- Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting).
- Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases.
- Practical experience building for live, non-mocked environments and handling multi-turn system interactions.
- Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors.
Nice to have
- Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output.
- Hands-on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems.
- High level of comfort implementing persistent state and session discovery to track agent progress.
- Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.
Remote working/work at home options are available for this role.
MLOps Engineer (Remote) (Liverpool) in London employer: Outlier AI
Outlier is an exceptional employer that champions innovation and collaboration in the AI sector, offering remote work flexibility that allows you to thrive from anywhere, including Liverpool. With a strong focus on employee growth, we provide opportunities to work on cutting-edge projects that shape the future of autonomous agents, fostering a culture of continuous learning and technical excellence. Join us to be part of a dynamic team where your contributions directly impact the advancement of AI technology in a supportive and engaging environment.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer (Remote) (Liverpool) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and MLOps community on LinkedIn or Twitter. Join relevant groups and participate in discussions to get your name out there and show off your passion for the field.
✨Tip Number 2
Showcase your skills! Create a portfolio of projects that highlight your experience with backend engineering and AI automation. This could be anything from GitHub repos to personal blogs explaining your thought process behind complex systems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with languages like Python or Java, and think about how you can explain your approach to building production-grade software.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace MLOps Engineer (Remote) (Liverpool) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the MLOps Engineer role. Highlight your experience in backend engineering and any relevant projects you've worked on that align with AI automation and complex systems integration.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples to show how you've built production-grade software or handled multi-turn system interactions. This will help us see your practical experience in action.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you're passionate about shaping the future of autonomous agents and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Apply Through Our Website:We encourage you to apply through our website for the best chance of being considered. It’s straightforward, and we want to make sure your application gets into the right hands quickly!
How to prepare for a job interview at Outlier AI
✨Know Your Tech Stack
Make sure you’re well-versed in the programming languages mentioned in the job description, like Python or JavaScript. Brush up on your SQL skills too, as you might be asked to demonstrate your understanding of databases during the interview.
✨Showcase Your Experience
Prepare specific examples from your past work that highlight your experience with backend engineering and AI automation. Be ready to discuss how you've built and maintained production-grade software, focusing on modular separation and complex systems integration.
✨Understand the Project
Familiarise yourself with Outlier's projects and their focus on training Large Language Models. Think about how your skills can contribute to shaping autonomous agents and be prepared to share your thoughts on the future of AI in this context.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the company’s projects. This shows your genuine interest and helps you gauge if the company is the right fit for you. Consider asking about their approach to integrating agents with live tools or how they handle privacy concerns.
