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- Tasks: Enhance AI/ML initiatives by developing software solutions and tackling real-world challenges.
- Company: Leading consulting firm in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a collaborative team and shape AI-powered products that make a global impact.
- Qualifications: Strong programming skills in Python and experience with LLMs and data science libraries.
- Other info: Dynamic work environment with exciting projects and career advancement opportunities.
The predicted salary is between 36000 - 60000 £ per year.
A leading consulting firm in the United Kingdom is seeking an AI/ML Engineer to enhance its AI/ML initiatives. This hands-on role emphasizes practical software engineering with Python, addressing real-world challenges such as expert recommendations and content extraction.
The ideal candidate should possess strong programming skills, a solid foundation in LLMs, and experience with data science libraries. Join a collaborative team and contribute to shaping AI-powered products with global impact.
AI/ML Engineer — Production LLMs & Data Pipelines employer: proSapient
Contact Detail:
proSapient Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer — Production LLMs & Data Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the AI/ML space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and data pipelines. We want to see your practical experience in action, so make it easy for potential employers to see what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and data science libraries. We recommend doing mock interviews with friends or using online platforms to get comfortable with the types of 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 by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI/ML Engineer — Production LLMs & Data Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your programming skills and experience with LLMs. We want to see how your background aligns with the role, so don’t be shy about showcasing relevant projects or achievements!
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 you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool projects involving Python or data science libraries, make sure to mention them! We’re keen to see practical examples of your work that demonstrate your problem-solving skills in real-world scenarios.
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’s super easy – just follow the prompts!
How to prepare for a job interview at proSapient
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with libraries like NumPy and Pandas, as well as any projects where you've implemented AI/ML solutions. Practical examples will show your hands-on experience.
✨Understand LLMs Thoroughly
Since the role focuses on production LLMs, dive deep into the latest advancements in this area. Be prepared to explain how you've worked with LLMs in the past, including any challenges you faced and how you overcame them. This will demonstrate your expertise and problem-solving abilities.
✨Showcase Your Data Pipeline Knowledge
Familiarise yourself with data pipeline architectures and best practices. Be ready to discuss how you've built or optimised data pipelines in previous roles. Highlighting your understanding of data flow and processing will set you apart from other candidates.
✨Emphasise Collaboration Skills
This role is all about teamwork, so be prepared to talk about your experiences working in collaborative environments. Share examples of how you've contributed to team projects and how you handle feedback. This will show that you're not just a tech whiz but also a great team player.
