At a Glance
- Tasks: Create and deploy machine learning models using Python and PyTorch.
- Company: Join a dynamic tech company in the heart of London.
- Benefits: Competitive pay up to £37, flexible contract role.
- Other info: Great opportunity for growth in a fast-paced environment.
- Why this job: Dive into the exciting world of AI and make a difference.
- Qualifications: Bachelor's in Computer Science and experience in Python and JavaScript.
The predicted salary is between 37000 - 37000 € per year.
Location: London, United Kingdom
Posted: 9 months ago
Tech stack:
- Frontend: React, JavaScript
- Backend: Python, PyTorch
Education:
Bachelor’s degree in Computer Science, Computer Engineering, or a related technical background.
Experience:
- Backend software engineering experience in Python.
- Frontend software engineering experience, preferably with JavaScript and React, including building and deploying user interfaces.
Compensation: up to £37
Role type: Contract
Visa sponsorship: Not provided
Machine Learning Software Engineer in London - Aquent employer: Java Script Works
Aquent is an exceptional employer for Machine Learning Software Engineers, offering a dynamic work culture in the heart of London. With a focus on innovation and collaboration, employees benefit from opportunities for professional growth and development, while enjoying a vibrant city atmosphere that fosters creativity and networking.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Software Engineer in London - Aquent
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning enthusiasts. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python and React. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your experience with PyTorch and software engineering. Practice common interview questions to boost your confidence.
✨Tip Number 4
Apply through our website! We make it easy for you to find roles that match your skills. Plus, it shows you're serious about joining our team. Don't miss out!
We think you need these skills to ace Machine Learning Software Engineer in London - Aquent
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, JavaScript, and React. We want to see how your skills match the job description, 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 machine learning and how your background makes you a great fit for our team. Keep it concise but engaging!
Showcase Your Projects:If you've worked on any cool projects involving machine learning or software engineering, make sure to mention them. We love seeing practical applications of your skills, so include links if possible!
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 Java Script Works
✨Know Your Tech Stack
Make sure you’re well-versed in Python, PyTorch, JavaScript, and React. Brush up on your backend and frontend skills, as you might be asked to demonstrate your knowledge during the interview.
✨Showcase Your Projects
Prepare to discuss any relevant projects you've worked on, especially those involving machine learning or software engineering. Be ready to explain your thought process, the challenges you faced, and how you overcame them.
✨Understand the Company’s Needs
Research Aquent and understand their focus areas in machine learning. Tailor your answers to show how your skills can directly benefit their projects and goals.
✨Practice Problem-Solving
Expect technical questions that test your problem-solving abilities. Practice coding challenges and algorithms related to machine learning and software engineering to boost your confidence.
