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 opportunities.
- 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) (Glasgow City) employer: Employer near you
Outlier is an exceptional employer that fosters a collaborative and innovative work culture, allowing MLOps Engineers to thrive in shaping the future of AI technology from the comfort of their own homes. With a strong emphasis on employee growth, we provide opportunities for continuous learning and development while working on cutting-edge projects with leading AI organisations. Our remote setup not only promotes work-life balance but also connects you with a diverse team of experts dedicated to pushing the boundaries of autonomous agents.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer (Remote) (Glasgow City)
✨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. Share your GitHub link when you apply through our website to give us a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and system design principles. Practice common MLOps scenarios and be ready to discuss how you've tackled complex integrations in the past.
✨Tip Number 4
Don’t forget to follow up after interviews! A quick thank-you email can go a long way in keeping you top of mind. Plus, it shows us that you're genuinely interested in the role and the company.
We think you need these skills to ace MLOps Engineer (Remote) (Glasgow City)
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 AI automation, and don’t forget to mention any relevant projects you've worked on that showcase your skills with languages like Python or Java.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about shaping the future of autonomous agents. Share specific examples of how your background aligns with our mission at Outlier and how you can contribute to our innovative projects.
Showcase Your Technical Skills:When filling out your application, be sure to highlight your technical skills clearly. Mention your experience with SQL databases and any hands-on work you've done with live environments. We love seeing candidates who can provide high-density technical feedback!
Apply Through Our Website:We encourage you to apply through our website for the best chance of being considered. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
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 and tools 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 help demonstrate your expertise.
✨Understand the Company’s Vision
Familiarise yourself with Outlier's mission and the types of AI agents they work with. Being able to articulate how your skills can contribute to their goals will show that you're genuinely interested in the role and the company.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and attention to detail. Practice explaining complex system behaviours clearly, as this is crucial for providing high-density feedback. Consider mock interviews to refine your responses.
