At a Glance
- Tasks: Develop and deploy AI solutions using cutting-edge technologies in a collaborative environment.
- Company: Join a forward-thinking tech company focused on impactful AI projects.
- Benefits: Enjoy competitive pay, flexible work, and a comprehensive benefits package.
- Other info: Dynamic team culture with continuous learning opportunities and social events.
- Why this job: Make a real impact in the AI field while growing your skills and career.
- Qualifications: Experience in MLOps, strong Python skills, and familiarity with ML lifecycle tools.
The predicted salary is between 50000 - 60000 £ per year.
Location: Erskine, Scotland, Hybrid
Security Clearance level: SC
Eligibility: Candidates must be UK national/sole British citizens and resided in the UK for 5 years or over.
Key Responsibilities:
- Strong proficiency in Python and ML libraries such as pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch.
- Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe.
- Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines.
- Experience working with distributed data processing using PySpark.
- Solid understanding of software engineering principles and version control (e.g., Git).
- Excellent problem‑solving skills and ability to work independently or in a team.
- Collaborate with cross‑functional teams to integrate AI solutions into scalable products.
- Ensure best practices in data engineering and contribute to architectural decisions.
- Support senior team members in identifying and addressing data science opportunities.
Required Skills & Experience:
- Proven experience in MLOps or DevOps roles within machine learning environments.
- Strong programming skills in Python, with hands‑on experience in PySpark and SQL.
- Deep understanding of ML lifecycle management and CI/CD best practices.
- Familiarity with cloud‑native ML platforms and scalable deployment strategies.
- Demonstrated relevant industry experience, including time spent in a similar role.
- Proficiencies in data cleansing, exploratory data analysis, and data visualization.
- Continuous learner that stays abreast with industry knowledge and technology.
Why Join Us?
- Work on impactful AI projects with real‑world applications.
- Be part of a collaborative and forward‑thinking team.
- Access to continuous learning and development opportunities.
- Flexible working arrangements and a supportive work culture.
Benefits:
- Competitive compensation.
- Pension scheme.
- DXC Select – Our comprehensive benefits package (includes private health/medical insurance, gym membership and more).
- Perks at Work (discounts on technology, groceries, travel and more).
- DXC incentives (recognition tools, employee lunches, regular social events etc).
Ready to shape the future of AI? Apply now and bring your expertise to a team that values innovation, creativity, and excellence.
MLOps Engineer: AI Deployment & Data Solutions (Hybrid) in Erskine employer: 慨正橡扯
Join a dynamic team in Erskine, Scotland, where you will work on impactful AI projects that drive real-world applications. Our collaborative and forward-thinking culture fosters continuous learning and development, offering flexible working arrangements and a comprehensive benefits package that includes private health insurance and discounts on various services. As an MLOps Engineer, you'll have the opportunity to grow your skills while contributing to innovative solutions in a supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer: AI Deployment & Data Solutions (Hybrid) in Erskine
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially those involving Python and ML libraries. 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 MLOps questions and practical scenarios. Practice explaining your past projects and how you tackled challenges—this will help you shine during the interview!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace MLOps Engineer: AI Deployment & Data Solutions (Hybrid) in Erskine
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences mentioned in the job description. Highlight your proficiency in Python and ML libraries, as well as any relevant MLOps or DevOps experience. We want to see how you fit into our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our needs. Don’t forget to mention your problem-solving skills and teamwork experience – we love collaboration!
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's model deployment or data processing with PySpark, we want to see what you've done. Real-world applications of your skills can really set you apart!
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 shows you’re keen to join our innovative team at StudySmarter!
How to prepare for a job interview at 慨正橡扯
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and the ML libraries mentioned in the job description. Be ready to discuss your experience with tools like TensorFlow, PyTorch, and ONNX. Having specific examples of projects where you've used these technologies will really impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare to talk about challenges you've faced in previous roles and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your analytical thinking and ability to work independently or as part of a team.
✨Familiarise Yourself with MLOps Practices
Since this role focuses on MLOps, make sure you understand the ML lifecycle management and CI/CD best practices. Be ready to discuss your experience with tools like MLflow and Azure ML Pipelines, and how you've implemented these in past projects.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team's current projects, the company culture, and opportunities for continuous learning. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
