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.
- Why this job: Join a team that’s redefining AI agents and make a real impact.
- Qualifications: 2+ years in backend engineering or AI automation; strong coding skills required.
The predicted salary is between 50000 - 70000 € 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) (Cambridge) in London employer: Employer near you
Outlier is an exceptional employer that fosters a collaborative and innovative work culture, allowing MLOps Engineers to thrive in a remote setting while shaping the future of AI technology. With a strong emphasis on employee growth, we provide opportunities for continuous learning and development, ensuring that our team members are at the forefront of advancements in AI and automation. Join us in Cambridge and be part of a dynamic team that values creativity, technical expertise, and meaningful contributions to cutting-edge projects.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer (Remote) (Cambridge) 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 on complex systems integration.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Python, SQL databases, and any live environments you've worked in. Practice explaining complex concepts in simple terms to demonstrate your communication skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Outlier and shaping the future of autonomous agents.
We think you need these skills to ace MLOps Engineer (Remote) (Cambridge) 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 projects that showcase your skills in AI automation or complex systems integration. We want to see how your background aligns with what we're looking for!
Showcase Your Skills:When writing your application, don’t just list your skills—show us how you've used them! Include specific examples of projects where you’ve built production-grade software or worked with SQL databases. This helps us understand your hands-on experience better.
Be Clear and Concise:We appreciate clarity! Make sure your application is easy to read and straight to the point. Use bullet points for key achievements and keep your language professional yet approachable. We want to get to know you without sifting through fluff!
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 the role. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Employer near you
✨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'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, especially any experience with complex systems integration or AI automation. Real-world examples will make your skills stand out!
✨Understand the Company’s Mission
Familiarise yourself with Outlier's work in improving AI agents. Being able to discuss how your background aligns with their goals will show your genuine interest and help you connect with the interviewers.
✨Prepare for Technical Questions
Expect questions that test your problem-solving skills and attention to detail. Be ready to tackle scenarios involving multi-turn system interactions or identifying subtle failures. Practising common technical interview questions can give you a leg up!
