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- Tasks: Deploy and scale machine learning models while collaborating with a dynamic team.
- Company: DXC Technology, a leader in AI and digital transformation.
- Benefits: Inclusive culture, continuous learning, and opportunities for career growth.
- Other info: Encourages applications from diverse backgrounds and offers supportive hiring processes.
- Why this job: Join a cutting-edge AI community and shape the future of technology.
- Qualifications: Strong Python skills and familiarity with ML libraries and frameworks.
The predicted salary is between 50000 - 70000 £ per year.
DXC Technology is committed to building diverse, inclusive teams. We welcome applications from all backgrounds and particularly encourage interest from women, underrepresented groups, and neurodivergent candidates. We offer reasonable adjustments throughout the hiring process and are dedicated to creating a supportive, accessible environment for everyone.
Location: Erskine, Newcastle, Farnborough or London. Candidates must be eligible for clearance.
Are you passionate about bringing machine learning solutions into real-world production environments? Do you enjoy collaborating with others to build scalable, reliable systems? We are looking for a Machine Learning Ops Engineer to join our growing team. This role is ideal for someone who enjoys solving complex problems, working cross-functionally, and continuously developing their technical expertise in a supportive environment. If you don’t meet every single requirement listed below, we still encourage you to apply. We value potential, curiosity, and a willingness to learn.
Key Responsibilities- Deploying, monitoring, and scaling machine learning models in production.
- Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products.
- Supporting the full ML lifecycle, from experimentation to deployment and optimisation.
- Applying best practices in data engineering and contributing to architectural decisions.
- Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency.
- Contributing to a culture of knowledge-sharing and continuous improvement.
- Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn.
- Experience with frameworks such as TensorFlow, Keras, or PyTorch.
- Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost.
- Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe).
- Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines.
- Experience working with distributed data processing (e.g., PySpark) and SQL.
- Understanding of software engineering best practices, including version control (Git).
- Knowledge of CI/CD principles in ML environments.
- Experience with cloud-native ML platforms is advantageous.
- Be part of a cutting-edge AI community driving digital transformation across the UK&I.
- Work at the intersection of business innovation and emerging AI technologies.
- Opportunity to shape the future of AI adoption within some of the UK’s most impactful industries.
- Collaborative, forward-thinking environment with continuous learning and development opportunities.
Machine Learning Ops Engineer in Shiremoor employer: DXC
Contact Detail:
DXC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Ops Engineer in Shiremoor
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on common ML concepts and be ready to discuss your past experiences. Practising with mock interviews can help you feel more confident and articulate during the real deal.
✨Tip Number 4
Don’t forget to apply through our website! We’re all about making the application process smooth and accessible. Plus, it shows you’re genuinely interested in joining our team at DXC Technology.
We think you need these skills to ace Machine Learning Ops Engineer in Shiremoor
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Machine Learning Ops Engineer role. Highlight your Python expertise and any relevant ML frameworks you've worked with. We want to see how you can bring your unique background to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for machine learning and how you’ve tackled complex problems in the past. Let us know why you’re excited about joining StudySmarter and how you can contribute to our mission.
Showcase Your Projects: If you’ve worked on any machine learning projects, don’t hold back! Include links to your GitHub or any other platforms where we can see your work. We love seeing practical applications of your skills and how you’ve used modern MLOps tools.
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 gives you a chance to explore more about our culture and values!
How to prepare for a job interview at DXC
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get familiar with the ML libraries mentioned in the job description. Be ready to discuss your experience with frameworks like TensorFlow or PyTorch, and have examples of how you've deployed models in production.
✨Showcase Your Collaboration Skills
Since this role involves working closely with data scientists and engineers, be prepared to share examples of past collaborations. Highlight how you’ve contributed to team projects and how you handle feedback and knowledge-sharing.
✨Understand the Full ML Lifecycle
Familiarise yourself with the entire machine learning lifecycle, from experimentation to deployment. Be ready to discuss best practices in data engineering and how you’ve applied CI/CD principles in your previous roles.
✨Ask Thoughtful Questions
Prepare some insightful questions about the company’s approach to AI and machine learning. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding diversity and inclusion.