At a Glance
- Tasks: Join a dynamic team to deploy cutting-edge Machine Learning models in retail.
- Company: Oliver Bernard, a leader in IT services and consulting.
- Benefits: Competitive pay of £550 per day, remote flexibility, and immediate start.
- Other info: Great opportunity for career growth in a collaborative tech culture.
- Why this job: Make an impact with innovative GenAI technologies in a fast-paced environment.
- Qualifications: Experience in ML deployments, API development, and cloud platforms required.
The predicted salary is between 39600 - 66000 £ per year.
ML Engineer (Outside IR35, £550 per day) employer: Oliver Bernard
At Oliver Bernard, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our remote and hybrid working options provide flexibility, while our commitment to employee growth ensures that you will have access to continuous learning opportunities in the rapidly evolving field of machine learning. Join us to be part of a forward-thinking team that values your contributions and supports your professional journey in the exciting retail technology sector.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer (Outside IR35, £550 per day)
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in retail or have experience with GenAI. A friendly chat can lead to referrals that double your chances of landing an interview.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects, especially those involving ML deployments or APIs, make sure to highlight them during interviews. We want to see what you can do, so don’t be shy!
✨Tip Number 3
Prepare for technical questions! Brush up on your knowledge of cloud services like AWS and GCP, as well as DevOps practices. Being able to discuss your experience with CI/CD and Docker will impress potential employers.
✨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 (Outside IR35, £550 per day)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with end-to-end ML deployments and any relevant projects you've worked on. We want to see how your skills align with the job description, so don’t be shy about showcasing your expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Mention your experience with GenAI models and cloud platforms like AWS or GCP, and how you can contribute to our team.
Showcase Problem-Solving Skills:In your application, highlight specific examples where you've tackled complex problems in ML or software development. We love seeing how you approach challenges and deliver scalable solutions!
Apply Through Our Website:To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Oliver Bernard
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around end-to-end deployments and GenAI models. Be ready to discuss your past projects and how you've tackled challenges in deploying scalable systems.
✨API Mastery is Key
Since the role involves building RESTful and GraphQL APIs, be prepared to talk about your experience with these technologies. Have examples ready that showcase how you've integrated GenAI systems with front-end and back-end platforms.
✨Show Off Your Problem-Solving Skills
Employers love a good problem-solver! Think of specific instances where you've delivered maintainable software under pressure. Highlight your approach to troubleshooting and how you ensure your solutions are scalable.
✨Communicate Like a Pro
As an effective communicator and team player, be ready to demonstrate your collaboration skills. Share experiences where you worked with cross-functional teams, especially in cloud environments like AWS or GCP, and how you contributed to DevOps practices.
