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For Companies At a Glance
- Tasks: Deploy and scale machine learning solutions in dynamic environments.
- Company: Join a fast-paced tech company with a focus on innovation.
- Benefits: Competitive salary, hybrid work options, and great benefits.
- Why this job: Make an impact by working on cutting-edge machine learning projects.
- Qualifications: Experience in ML operations and a passion for tech.
- Other info: Exciting career growth opportunities in a collaborative team.
The predicted salary is between 36000 - 60000 £ per year.
Job Description
Location: Newcastle, England or Erskine, Scotland
Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out.
Type:Full-Time
Remote Work:Hybrid options available
Salary:Competitive + Benefits
About the Role
Are you passionate about deploying and scaling machine learning solutions in production environments? Do you thrive in a fast-paced, tech-driven setting? Were looking for a talented OPS Engineer to join our growing teams in Erskine or Newcast…
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Data/ML Ops Engineer employer: DXC Technology
Contact Detail:
DXC Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data/ML Ops Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and data ops. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios specific to Data/ML Ops. Practise explaining your thought process clearly; it’s all about demonstrating your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Data/ML Ops Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data/ML Ops Engineer role. Highlight relevant experience and skills that match the job description. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about deploying machine learning solutions and how you thrive in fast-paced environments. Let us know what makes you the perfect fit for our team.
Showcase Your Projects: If you've worked on any cool projects related to data or machine learning, make sure to mention them! We love seeing practical examples of your work, so don’t hold back on sharing your achievements.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Don’t wait too long – we can’t wait to hear from you!
How to prepare for a job interview at DXC Technology
✨Know Your Tech Inside Out
As a Data/ML Ops Engineer, you'll need to be well-versed in machine learning frameworks and deployment tools. Brush up on the latest technologies and be ready to discuss your hands-on experience with them during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to tackle hypothetical scenarios related to scaling ML solutions. Think about past challenges you've faced and how you overcame them. This will demonstrate your critical thinking and adaptability in a fast-paced environment.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's tech stack, team dynamics, and future projects. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.
✨Highlight Collaboration Experience
In a hybrid work setting, teamwork is crucial. Be ready to share examples of how you've successfully collaborated with cross-functional teams in the past. This will illustrate your ability to thrive in a tech-driven setting and contribute to the team's success.
