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- Tasks: Build and maintain ML pipelines while owning model lifecycles.
- Company: Dynamic tech firm in Greater London with a focus on innovation.
- Benefits: Join a high-trust team that values autonomy and creativity.
- Why this job: Drive the integration of AI features into real-world systems.
- Qualifications: 3+ years of ML engineering experience and strong Python skills.
- Other info: Collaborate closely with engineers in a supportive environment.
The predicted salary is between 42000 - 84000 £ per year.
A dynamic technology firm in Greater London is seeking an Applied AI Engineer focused on building and maintaining ML and agentic data pipelines. You will own model lifecycles, collaborate closely with engineers, and drive the integration of AI features into production systems.
The ideal candidate has over 3 years of ML engineering experience and strong Python skills. Join a high-trust, low-ego team that values autonomy and innovation in delivering cutting-edge AI solutions.
Production AI Engineer: Own End-to-End ML Pipelines in London employer: Boam AI
Contact Detail:
Boam AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production AI Engineer: Own End-to-End ML Pipelines 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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects and pipelines. This is your chance to demonstrate your Python prowess and how you've tackled real-world problems. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for those interviews! Brush up on common ML concepts and be ready to discuss your past experiences. Practice coding challenges and be prepared to explain your thought process. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates. Tailor your application to highlight your experience with model lifecycles and AI integration – it’ll make you stand out!
We think you need these skills to ace Production AI Engineer: Own End-to-End ML Pipelines in London
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your ML engineering experience in your application. We want to see how your skills and past projects align with the role, so don’t hold back on showcasing your Python prowess!
Tailor Your Application: Take a moment to customise your application for us. Mention specific projects or experiences that relate to building and maintaining ML pipelines. This shows us you’re genuinely interested in the position and understand what we do.
Be Authentic: We value authenticity, so let your personality shine through in your written application. Share your passion for AI and innovation, and don’t be afraid to express why you want to join our dynamic team!
Apply Through Our Website: To make sure your application gets to us directly, apply through our website. It’s the best way for us to review your details and get you into the process smoothly. We can’t wait to hear from you!
How to prepare for a job interview at Boam AI
✨Know Your ML Pipelines
Make sure you can discuss your experience with end-to-end machine learning pipelines in detail. Be ready to explain how you've built, maintained, and optimised these systems in previous roles. This will show that you understand the entire lifecycle of a model.
✨Showcase Your Python Skills
Since strong Python skills are crucial for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so brush up on your Python syntax and libraries commonly used in ML, like NumPy and Pandas.
✨Collaboration is Key
This position involves working closely with engineers, so be prepared to discuss your teamwork experiences. Share examples of how you've collaborated on projects, resolved conflicts, or contributed to a team’s success. Highlighting your ability to work in a high-trust, low-ego environment will resonate well.
✨Emphasise Innovation
The company values innovation, so think about how you've driven new ideas or improvements in your past roles. Be ready to share specific examples where your innovative thinking led to successful AI solutions or enhancements in production systems.
