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- Tasks: Shape the future of software development with AI and ML technologies.
- Company: Join JetBrains, a leader in innovative software solutions.
- Benefits: Enjoy competitive salary and startup-like autonomy.
- Other info: Be part of a dynamic team driving cutting-edge technology.
- Why this job: Make a real impact by defining the research agenda in ML.
- Qualifications: 5+ years in ML/AI, hands-on LLM experience, strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
JetBrains is looking for a top-class ML Engineer to shape the future of software development through AI and ML technologies. You will define the research agenda and own the AI engineering stack.
Responsibilities include:
- Designing LLM solutions
- Establishing MLOps practices
The ideal candidate should have at least five years of experience in ML/AI systems, hands-on LLM experience, and strong Python skills.
We offer a competitive salary and startup-like autonomy.
Founding ML Engineer: Build a Living Semantic Layer in London employer: JetBrains
Contact Detail:
JetBrains Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Founding ML Engineer: Build a Living Semantic Layer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving LLMs. This is your chance to demonstrate your hands-on experience and Python prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML interview questions and be ready to discuss your past projects in detail. We want to see how you think!
✨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 that extra step to engage with us directly.
We think you need these skills to ace Founding ML Engineer: Build a Living Semantic Layer in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with ML/AI systems and LLMs in your application. We want to see your strong Python skills shine through, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. Mention how your past experiences align with the responsibilities of shaping AI engineering stacks and MLOps practices.
Be Authentic: Let your personality come through in your written application. We’re looking for someone who’s not just qualified but also a great fit for our team culture at StudySmarter.
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 us!
How to prepare for a job interview at JetBrains
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially around LLMs. Be ready to discuss your past projects and how you've applied ML/AI technologies in real-world scenarios. This will show that you not only understand the theory but can also implement it effectively.
✨Show Off Your Python Skills
Since strong Python skills are a must for this role, be prepared to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your thought process behind a piece of code. Practising common algorithms and data structures in Python can really help you shine.
✨Understand MLOps Practices
Familiarise yourself with MLOps principles and tools. Be ready to discuss how you would establish MLOps practices in a team setting. This could include topics like model deployment, monitoring, and versioning, which are crucial for maintaining robust ML systems.
✨Ask Insightful Questions
Prepare some thoughtful questions about JetBrains' approach to AI and ML. This shows your genuine interest in the company and the role. You might ask about their current projects, challenges they face in ML engineering, or how they envision the future of software development with AI.