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- Tasks: Architect and maintain production-grade ML services while collaborating on product challenges.
- Company: Join bloomon, a forward-thinking company in Greater London.
- Benefits: Enjoy flexible working, generous holidays, training opportunities, and ClassPass membership.
- Other info: Dynamic team environment with great growth potential.
- Why this job: Make an impact by enhancing ML models and tackling real-world challenges.
- Qualifications: Solid grounding in machine learning, strong Python skills, and SQL experience.
The predicted salary is between 50000 - 70000 £ per year.
bloomon is seeking a skilled Machine Learning Engineer in Greater London to architect and maintain production-grade ML services. This role involves collaborating with various teams to tackle product-related challenges and enhance ML models.
Ideal candidates should have:
- A solid grounding in machine learning
- Strong programming skills in Python
- Experience with SQL
The company offers flexible working arrangements, generous holiday, training opportunities, and additional perks like ClassPass membership.
ML Engineer: Build Low-Latency Models & MLOps in London employer: Bloomon
Contact Detail:
Bloomon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer: Build Low-Latency Models & MLOps in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at bloomon on LinkedIn. A friendly chat can give us insider info about the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your best ML projects. We want to see how you’ve tackled real-world problems, especially those involving low-latency models and MLOps.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on Python and SQL. We recommend doing mock interviews with friends or using online platforms to simulate the experience.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace ML Engineer: Build Low-Latency Models & MLOps in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your machine learning expertise and programming skills in Python. We want to see how you can tackle product-related challenges, so don’t hold back on showcasing your experience!
Tailor Your Application: Take a moment to customise your application for the ML Engineer role. Mention specific projects or experiences that relate to building low-latency models and MLOps. This helps us see how you fit into our team!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that are easy to read. Avoid jargon unless it’s relevant to the role!
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!
How to prepare for a job interview at Bloomon
✨Know Your ML Fundamentals
Make sure you brush up on your machine learning concepts. Be ready to discuss algorithms, model evaluation metrics, and the intricacies of low-latency models. This will show that you have a solid grounding in the field and can contribute effectively.
✨Showcase Your Python Skills
Since strong programming skills in Python are essential for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem or explain your previous projects, so have examples ready that highlight your expertise in Python and any relevant libraries.
✨Familiarise Yourself with SQL
As SQL experience is mentioned in the job description, make sure you can discuss how you've used SQL in past projects. Be prepared to answer questions about database management and data retrieval, as these skills will be crucial for collaborating with other teams.
✨Emphasise Collaboration and Problem-Solving
This role involves working with various teams to tackle product-related challenges. Think of examples from your past experiences where you successfully collaborated with others to solve complex problems. Highlighting your teamwork skills will show that you're a good fit for their culture.