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- Tasks: Join a cutting-edge AI startup and develop high-volume ML pipelines.
- Company: Exciting voice AI startup with multi-million funding based in London.
- Benefits: Competitive salary, flexible office days, and opportunities for growth.
- Why this job: Make an impact in the AI field while working with innovative technologies.
- Qualifications: Bachelor’s degree in Computer Science and strong Python skills required.
- Other info: Collaborative environment with a focus on teamwork and innovation.
The predicted salary is between 60000 - 80000 £ per year.
A newly established Voice AI startup with multi-million funding is looking to hire an AI / ML Engineer to focus on their ML pipelines which process very high-volume events at scale.
Our client is looking for an individual with significant experience as either an AI Engineer or Machine Learning Engineer with clear evidence of shipping LLM powered ML products.
To be suitable for this role you will require the below:
- Key Requirements
- Bachelor’s degree in Computer Science, Machine Learning, or a related field
- Excellent experience as an ML or AI Engineer, with evidence of shipping production systems
- Strong Python skills and experience with FastAPI
- Experience working with modern MLOps tools, ideally Kubeflow
- Strong experience working closely with LLMs (including fine-tuning, RAG, prompt engineering)
- Strong problem-solving skills and ability to communicate technical trade-offs clearly
- Collaborative mindset with experience working across technical and non-technical teams
This position is a permanent role, based in London, with 3-4 days a week in the company's office. The role offers a salary between £60,000 - £80,000.
AI / ML Engineer employer: Ventula Consulting
Contact Detail:
Ventula Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI / ML Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and ML community, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and ML pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and MLOps tools like Kubeflow. Practice coding challenges and be ready to discuss your past projects in detail—employers love to hear about real-world applications!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, it’s a great way to get noticed by hiring managers who are looking for talent just like yours.
We think you need these skills to ace AI / ML Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience as an AI or ML Engineer. We want to see clear evidence of your work with LLMs and production systems, so don’t hold back on those details!
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 skills align with our needs. Let us know what excites you about working in a startup environment.
Showcase Your Projects: If you've worked on any relevant projects, especially those involving ML pipelines or FastAPI, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Ventula Consulting
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and be ready to discuss your experience with FastAPI. Be prepared to dive deep into your past projects, especially those involving LLMs, and explain how you tackled challenges in shipping production systems.
✨Showcase Your Problem-Solving Skills
During the interview, expect to face some technical scenarios. Practice articulating your thought process when solving problems, especially around ML pipelines and MLOps tools like Kubeflow. This will demonstrate your analytical abilities and how you approach complex issues.
✨Communicate Clearly
Since the role requires collaboration across technical and non-technical teams, practice explaining technical concepts in simple terms. This will show that you can bridge the gap between different stakeholders and ensure everyone is on the same page.
✨Be Ready for Questions on Collaboration
Think of examples from your previous roles where you worked closely with others. Highlight your collaborative mindset and how you contributed to team success, especially in cross-functional settings. This will resonate well with the startup's culture.