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- Tasks: Deploy AI models and optimise performance in a cutting-edge tech environment.
- Company: Join Aramco's Digital & AI Centre of Excellence in Saudi Arabia.
- Benefits: Permanent role with competitive salary and opportunities for growth.
- Other info: Work with advanced tools like Kubernetes, Docker, and Python.
- Why this job: Be at the forefront of AI/ML technology and make a significant impact.
- Qualifications: Master's degree and 8 years of experience, including LLM deployment.
The predicted salary is between 80000 - 120000 £ per year.
Aramco is seeking an AI/ML/LLM Systems Engineer for their Digital & AI Center of Excellence based in Saudi Arabia. This permanent role requires a master's degree and 8 years of experience, including 4 years in LLM deployment.
Responsibilities include:
- Deploying AI models
- Optimizing inference performance
- Implementing CI/CD pipelines
The ideal candidate will demonstrate proficiency in tools such as Kubernetes, Docker, and Python, and have experience in managing high-performance computing environments.
Enterprise AI/ML Systems Engineer — LLM Inference in London employer: Aramco
Contact Detail:
Aramco Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Enterprise AI/ML Systems Engineer — LLM Inference in London
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space, especially those at Aramco or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got experience with Kubernetes, Docker, or Python, make sure to highlight specific projects where you used these tools. Real-world examples can make you stand out.
✨Tip Number 3
Prepare for technical interviews by brushing up on LLM deployment and CI/CD pipelines. We recommend doing mock interviews with friends or using online platforms to get comfortable with the questions you might face.
✨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 take the initiative to connect directly with us.
We think you need these skills to ace Enterprise AI/ML Systems Engineer — LLM Inference in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the job description. Highlight your experience with LLM deployment and any relevant tools like Kubernetes and Docker. 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 AI/ML and how your skills can contribute to our Digital & AI Centre of Excellence. Keep it engaging and personal, so we get a sense of who you are.
Showcase Your Projects: If you've worked on any projects related to AI models or CI/CD pipelines, make sure to mention them! We love seeing real-world applications of your skills, so don’t hold back on sharing your achievements.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Aramco
✨Know Your AI/ML Stuff
Make sure you brush up on your knowledge of AI and ML, especially around LLM deployment. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show that you not only understand the theory but also have practical experience.
✨Show Off Your Technical Skills
Since the role requires proficiency in tools like Kubernetes, Docker, and Python, be prepared to talk about your experience with these technologies. You might even want to bring examples of how you've used them to optimise inference performance or manage high-performance computing environments.
✨Demonstrate CI/CD Knowledge
As implementing CI/CD pipelines is part of the job, make sure you can explain your understanding of continuous integration and continuous deployment. Share any relevant experiences where you've successfully implemented these practices in your previous roles.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the team, the projects you'll be working on, and the company's vision for AI/ML. This shows your genuine interest in the role and helps you assess if it's the right fit for you.