At a Glance
- Tasks: Shape the future of AI by training advanced generative systems and optimising workflows.
- Company: Join Outlier, a leader in AI innovation with a collaborative remote culture.
- Benefits: Enjoy competitive pay, flexible remote work, and opportunities for professional growth.
- Other info: Dynamic role with potential for career advancement in a fast-paced environment.
- Why this job: Make a real impact on cutting-edge AI projects and enhance your tech skills.
- 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 using MEMORY.md to track agent progress.
- Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.
MLOps Engineer (Remote) (Brighton) employer: Outlier AI
At Outlier, we pride ourselves on being an exceptional employer, offering a dynamic remote work environment that fosters innovation and collaboration. Our culture is built on continuous learning and growth, providing employees with ample opportunities to enhance their skills in cutting-edge AI technologies while working alongside industry leaders. With a focus on meaningful projects that shape the future of autonomous agents, we ensure that our team members are not only valued but also empowered to make a significant impact in the field.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer (Remote) (Brighton)
✨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 that highlights your projects, especially those involving backend engineering or AI automation. This is your chance to demonstrate your expertise in building production-grade software and handling 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 of examples where you've tackled real-world problems using your skills.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at Outlier. Tailor your application to highlight how your background aligns with our mission to improve AI agents.
We think you need these skills to ace MLOps Engineer (Remote) (Brighton)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the MLOps Engineer role. Highlight your backend engineering experience and any work with AI automation or complex systems integration. We want to see how you can contribute to our projects!
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 your work with modular software and multi-turn system interactions to show us what you bring to the table.
Show Off Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention the programming languages you’re comfortable with, especially Python, JavaScript, Go, or Java. If you've worked with SQL databases or integrated agents with live tools, let us know!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and keep track of it. Plus, it shows you’re keen on joining our team at StudySmarter!
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'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 modular separation and how you tackled complex system integrations. Real-world examples will make your experience stand out!
✨Understand the Company’s Mission
Familiarise yourself with Outlier's work in AI and autonomous agents. Being able to articulate how your skills can contribute to their projects will show that you’re genuinely interested and aligned with their goals.
✨Prepare for Technical Questions
Expect questions that test your problem-solving skills and attention to detail. Be ready to discuss how you would handle multi-turn interactions and identify subtle failures in systems. Practising these scenarios can give you a leg up!
