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For Companies At a Glance
- Tasks: Design and implement cutting-edge AI solutions and lead client delivery.
- Company: Dynamic tech firm in London with a hybrid work model.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Mentorship opportunities and a culture of excellence await you.
- Why this job: Join a team shaping the future of AI and make a real impact.
- Qualifications: 6+ years in AI engineering with strong Python and LLM experience.
The predicted salary is between 48000 - 72000 £ per year.
Work Mode: Hybrid
Location: London
What You’ll Do
- Design & Architect AI Solutions
- Architect and implement advanced LLM systems (RAG, fine-tuning, agents, copilots) from concept to production.
- Design end-to-end AI pipelines encompassing data processing, model evaluation, deployment, and monitoring.
- Select and optimize the use of commercial and open-source LLMs (e.g., GPT, Claude, LLaMA) for performance, cost, and security.
- Build scalable, secure, and cost-efficient cloud-based AI architectures.
- Lead Client Delivery & Advisory
- Act as the primary technical point of contact for enterprise clients, translating business needs into technical requirements and solutions.
- Lead workshops, solution walkthroughs, and presentations for both technical and executive audiences.
- Own project delivery timelines, manage risks, and ensure projects are delivered on time and within scope.
- Drive Team Leadership & Growth
- Mentor and coach junior and mid-level data scientists and ML engineers.
- Contribute to hiring, onboarding, and the establishment of technical standards and best practices.
- Lead and scale a high-performing AI delivery team, fostering a culture of excellence.
- Establish robust practices for code quality, documentation, model governance, and MLOps.
Must-Have Qualifications
- 6+ years of professional experience in data science, machine learning, or AI engineering.
- Proven, hands-on experience building and deploying LLM applications (RAG, agents, fine-tuning) in production environments.
- Expertise in Python and deep learning frameworks (PyTorch or TensorFlow).
- Deep technical knowledge of prompt engineering, retrieval-augmented generation (RAG) architectures, fine-tuning, and inference optimization.
- Solid experience deploying and monitoring models in production on a major cloud platform (AWS, Azure, or GCP).
- Proven client-facing, consulting, or stakeholder management experience with excellent communication and presentation skills.
Nice-to-Have Qualifications
- Experience directly mentoring or leading technical teams.
- Strong MLOps skills (CI/CD, containerization, model monitoring) using tools like MLflow, Weights & Biases, etc.
- Experience working in regulated industries (finance, healthcare, enterprise SaaS).
- Knowledge of AI governance, responsible AI, data privacy, and security standards.
- Experience scoping projects, estimating timelines, and writing technical proposals.
What Success Looks Like In Your First Year
- Successfully deliver multiple end-to-end LLM projects for key clients, achieving defined success metrics.
- Become the go-to trusted AI advisor for a portfolio of clients and internally for company leadership.
- Design and socialize reusable frameworks, patterns, and best practices that elevate our team's efficiency and quality.
- Take on clear leadership responsibilities for a growing team, contributing directly to their development and the team's productivity gains.
AIML Engineer employer: Leute Passen Technologies
Contact Detail:
Leute Passen Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AIML Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AIML space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and AI solutions. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and client-facing skills. Practice explaining complex concepts in simple terms, as you'll need to translate technical jargon for clients. We want you to shine in those interviews!
✨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. Let’s get you that AIML Engineer role!
We think you need these skills to ace AIML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AIML Engineer role. Highlight your experience with LLMs, Python, and any relevant projects you've worked on. We want to see how your skills match 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 AI and how your experience aligns with our needs. Don’t forget to mention any client-facing roles you've had – we love that stuff!
Showcase Your Projects: If you've worked on any cool AI projects, make sure to include them in your application. Whether it's fine-tuning models or building pipelines, we want to see what you've done and how you can bring that expertise to our team.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Leute Passen Technologies
✨Know Your LLMs Inside Out
Make sure you’re well-versed in the latest large language models like GPT, Claude, and LLaMA. Be ready to discuss their strengths, weaknesses, and how you’ve used them in past projects. This shows you’re not just familiar with the tech but can also apply it effectively.
✨Showcase Your Client-Facing Skills
Since this role involves acting as a primary technical point of contact for clients, prepare examples of how you've translated complex technical concepts into business solutions. Highlight your experience leading workshops or presentations, as this will demonstrate your ability to communicate effectively with both technical and non-technical audiences.
✨Demonstrate Your Leadership Experience
Be ready to talk about your mentoring and coaching experiences. Share specific instances where you’ve helped junior team members grow or contributed to building a high-performing team. This will show that you’re not just a tech whiz but also someone who can lead and inspire others.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions around AI pipelines, model evaluation, and MLOps practices. Brush up on your knowledge of CI/CD processes and tools like MLflow or Weights & Biases. Being able to discuss these topics confidently will set you apart as a strong candidate.