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- Tasks: Scale unstructured data pipelines and enhance AWS infrastructure for AI projects.
- Company: Leading financial data solutions provider in Greater London.
- Benefits: Supportive work environment with great career development opportunities.
- Why this job: Join a dynamic team and work on cutting-edge AI and machine learning projects.
- Qualifications: 3-5 years in software engineering, strong AWS and NLP knowledge required.
- Other info: Collaborative culture focused on innovation and growth.
The predicted salary is between 42000 - 84000 £ per year.
A leading financial data solutions provider in Greater London is seeking a Software Engineer specializing in AI and machine learning. The role involves scaling unstructured data pipelines, enhancing AWS infrastructure, and collaborating on ML projects.
Ideal candidates will have:
- 3-5 years of experience in software engineering
- A strong knowledge of AWS and NLP
- Proven experience with ML model deployment
The company offers a supportive work environment and ample opportunities for career development.
ML Engineer - Python/NLP for Production AI & Knowledge Graphs in London employer: FactSet Research Systems Inc.
Contact Detail:
FactSet Research Systems Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer - Python/NLP for Production AI & Knowledge Graphs in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with AI and machine learning. Attend meetups or webinars to connect with potential employers and get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS and NLP. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and AWS services. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to stay updated on new roles in the field.
We think you need these skills to ace ML Engineer - Python/NLP for Production AI & Knowledge Graphs in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in software engineering, especially with Python and NLP. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and machine learning, and how your background makes you a perfect fit for our team. Let us know what excites you about this role!
Showcase Your AWS Knowledge: Since the role involves enhancing AWS infrastructure, make sure to mention any relevant experience you have with AWS services. We love seeing candidates who can demonstrate their technical prowess in this area!
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 our team!
How to prepare for a job interview at FactSet Research Systems Inc.
✨Know Your Tech Inside Out
Make sure you brush up on your Python and NLP skills. Be ready to discuss specific projects where you've deployed ML models or worked with unstructured data. The more detailed examples you can provide, the better!
✨AWS Familiarity is Key
Since the role involves enhancing AWS infrastructure, be prepared to talk about your experience with AWS services. Think of scenarios where you've optimised cloud resources or scaled applications, as this will show your practical knowledge.
✨Collaboration is Crucial
This position requires teamwork on ML projects, so highlight your collaborative experiences. Share stories about how you've worked with cross-functional teams, tackled challenges together, and contributed to successful outcomes.
✨Show Your Passion for Learning
The company values career development, so express your enthusiasm for continuous learning. Mention any recent courses, certifications, or personal projects related to AI and machine learning that demonstrate your commitment to growth in this field.
