At a Glance
- Tasks: Help shape the future of AI by training advanced generative systems.
- Company: Outlier, a leader in AI innovation and collaboration.
- Benefits: Remote work options, competitive salary, and opportunities for professional growth.
- Other info: Work in a fast-paced environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team and make a real impact on cutting-edge AI projects.
- 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 using 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) (Bristol) in London employer: Outlier AI
Outlier is an exceptional employer that fosters a collaborative and innovative work culture, allowing MLOps Engineers to thrive in a remote setting from Bristol. With a strong focus on employee growth, we offer opportunities to work on cutting-edge AI projects that shape the future of autonomous agents, while providing a supportive environment that values technical expertise and creativity. Join us to be part of a team that not only pushes the boundaries of technology but also prioritises your professional development and well-being.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer (Remote) (Bristol) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or attend virtual meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that MLOps Engineer gig.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI automation or complex systems integration. We love seeing real-world applications of your expertise, so make sure to highlight your best work.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and system design principles. We recommend practicing common algorithms and system architecture questions to impress your interviewers with your knowledge and problem-solving abilities.
✨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’re always on the lookout for passionate candidates who want to shape the future of autonomous agents.
We think you need these skills to ace MLOps Engineer (Remote) (Bristol) 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 showcase your skills in AI automation and complex systems integration.
Showcase Your Skills:We want to see your command of programming languages like Python or JavaScript. Include specific examples of how you've used these languages in real-world applications, especially in building production-grade software.
Detail Your Experience:When describing your past roles, focus on your practical experience with live environments and multi-turn system interactions. This will help us understand how you handle complex workflows and provide technical feedback.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape the future of autonomous agents.
How to prepare for a job interview at Outlier AI
✨Know Your Tech Stack
Make sure you’re well-versed in the programming languages and technologies mentioned in the job description, like Python or JavaScript. Brush up on your SQL skills too, as you'll likely be asked about your experience with databases during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built production-grade software. Highlight your role in these projects, focusing on how you handled complex systems integration and any challenges you overcame. Real-world examples will make your experience more relatable.
✨Understand the Company’s Mission
Familiarise yourself with Outlier's work in AI and autonomous agents. Be ready to discuss how your skills can contribute to their goals, especially in training Large Language Models. Showing genuine interest in their projects can set you apart from other candidates.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and attention to detail. Practice explaining complex system behaviours clearly and concisely, as this will demonstrate your ability to provide high-density feedback, which is crucial for the role.
