At a Glance
- Tasks: 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: Dynamic remote environment with exciting projects and career advancement.
- Why this job: Join us to make a real impact on cutting-edge AI technology.
- 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. Do you want to shape the future of autonomous agents like OpenClaw? 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.
ML Engineer (Remote) (Cambridge) employer: Outlier AI
Outlier is an exceptional employer that fosters a collaborative and innovative work culture, allowing ML Engineers to contribute to groundbreaking projects in AI. With remote working options available, employees enjoy flexibility while being part of a team that values professional growth and offers opportunities to work with leading AI organisations. Join us to shape the future of autonomous agents in a supportive environment that encourages creativity and technical excellence.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer (Remote) (Cambridge)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community on LinkedIn or Twitter. Join relevant groups and participate in discussions to get your name out there. You never know who might have a lead on that perfect job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs or complex systems integration. Share it during interviews or even on your social media to catch the eye of potential employers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your coding skills and system design principles. Practice common ML engineering problems and be ready to discuss your past experiences in detail. We want to see how you think and solve problems!
✨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 are proactive about their job search. So, hit that apply button and let’s get started!
We think you need these skills to ace ML Engineer (Remote) (Cambridge)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the ML 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!
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 LLMs or any relevant projects that demonstrate your expertise. Let us know why you’re the perfect fit!
Showcase Your Technical Skills:Don’t forget to highlight your command of programming languages like Python or JavaScript. If you've worked with SQL databases or built production-grade software, make sure to mention it! We love seeing practical experience that relates directly to our projects.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy to do!
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 these projects, focusing on how you handled complex system integrations and any challenges you overcame.
✨Understand the Company’s Mission
Familiarise yourself with Outlier's work in AI and autonomous agents. Being able to discuss their projects, like OpenClaw, will show your genuine interest and help you connect your skills to their goals.
✨Prepare for Technical Questions
Expect questions that test your problem-solving skills and attention to detail. Be ready to explain how you would approach identifying failures in systems or integrating agents with live tools, as these are crucial for the role.
