At a Glance
- Tasks: Design and deploy real-world AI solutions in complex environments.
- Company: Join a high-trust, collaborative team focused on impactful AI.
- Benefits: Competitive salary, professional growth, and hands-on experience.
- Other info: Opportunity to work with cutting-edge technology in secure environments.
- Why this job: Tackle challenging AI problems and influence technical direction.
- Qualifications: Strong experience in AI/ML and problem-solving skills required.
The predicted salary is between 80000 - 100000 £ per year.
We're looking for a hands-on Applied AI Scientist to design, build and deploy real-world AI solutions in complex, constrained environments. This is a senior technical role focused on delivery and impact - ideal for someone who enjoys solving challenging problems and influencing through expertise.
What you'll be doing:
- Designing, building and deploying AI/ML solutions end-to-end
- Working closely with users to translate real-world problems into technical solutions
- Developing models using production-grade Python
- Deploying AI solutions in secure, offline / air-gapped environments
- Working with GPU hardware for training and inference
- Optimising performance, scalability and system resilience
- Influencing technical direction through delivery and expertise
- Sharing knowledge and supporting continuous learning across the team
What we're looking for:
- Strong experience as an Applied AI Scientist / Data Scientist
- Experience building and deploying AI solutions without reliance on cloud-managed services
- Solid understanding of modern AI/ML techniques
- Experience with GPU-based model training/inference
- Ability to work independently and own delivery end-to-end
- Strong problem-solving skills and stakeholder engagement
Nice to have:
- Experience in secure or air-gapped environments
- Experience with edge or constrained systems
- Background delivering AI in real-world operational environments
- Ability to influence technical decisions without formal authority
- Work on complex, real-world AI challenges
- High-trust, collaborative environment focused on impact
- Opportunity to shape solutions in cutting-edge, constrained environments
If you're a hands-on AI engineer who thrives on solving real problems and delivering impact, apply now.
Principal Applied AI Scientist employer: Lorien
Join a forward-thinking organisation that values innovation and collaboration, where as a Principal Applied AI Scientist, you will have the opportunity to work on cutting-edge AI solutions in secure environments. Our culture fosters continuous learning and professional growth, ensuring that you can influence technical direction while tackling complex challenges. With a focus on impactful delivery, we offer a supportive atmosphere that encourages creativity and problem-solving.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Applied AI Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow AI enthusiasts. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio of your AI projects, especially those that demonstrate your ability to solve real-world problems. This will give potential employers a taste of what you can do and how you think.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you approach complex problems!
✨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 and making an impact in the AI space.
We think you need these skills to ace Principal Applied AI Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience as an Applied AI Scientist. Focus on specific projects where you've designed and deployed AI solutions, especially in complex environments. We want to see how your skills align with the role!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your expertise can make a real impact at StudySmarter. Don’t forget to mention any experience with GPU hardware or secure environments.
Showcase Problem-Solving Skills:In your application, highlight instances where you've tackled challenging problems. We love seeing how you’ve influenced technical decisions and delivered results, so share those stories that demonstrate your problem-solving prowess!
Apply Through Our Website:We encourage you to apply directly 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 you’re keen on joining our team!
How to prepare for a job interview at Lorien
✨Know Your AI Inside Out
Make sure you brush up on the latest AI/ML techniques and be ready to discuss how you've applied them in real-world scenarios. Prepare examples of your past projects, especially those involving GPU hardware and offline environments, as these will resonate well with the interviewers.
✨Showcase Problem-Solving Skills
Be prepared to tackle hypothetical problems during the interview. Think through your approach to designing and deploying AI solutions in constrained environments. This will demonstrate your ability to think critically and apply your expertise effectively.
✨Engage with Stakeholders
Highlight your experience in translating user needs into technical solutions. Be ready to discuss how you've collaborated with users or stakeholders in previous roles, as this shows your ability to influence and communicate effectively without formal authority.
✨Demonstrate Continuous Learning
Share how you keep up with advancements in AI and ML. Discuss any recent courses, workshops, or projects that have contributed to your knowledge. This not only shows your passion for the field but also aligns with the company's focus on continuous learning and knowledge sharing.
