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- Tasks: Join us as an MLOPS Engineer, focusing on Azure and machine learning projects.
- Company: Work with a leading consultancy known for innovation and excellence in IT solutions.
- Benefits: Enjoy flexible remote work options and a dynamic team environment.
- Why this job: Be part of cutting-edge technology, enhancing your skills in a collaborative culture.
- Qualifications: Experience with Azure, machine learning frameworks, and strong programming skills are essential.
- Other info: This is a 6-month rolling contract with a mix of remote and on-site work.
The predicted salary is between 48000 - 72000 £ per year.
MLOPS Engineer
My client, a large consultancy, is in need of an MLOPS Engineer for a 6 month rolling contract inside IR35, offering 2 days per week remote but requiring 3 days per week on-site in Reading.
The ideal candidate will have good experience in the IT industry with a strong focus on Azure-based architecture, Machine Learning, and MLOps, Deep experience with Azure services, especially Azure Machine Learning, Azure Kubernetes Service (AKS), Azure Data Lake, and Azure Synapse, Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn, Strong understanding of MLOps concepts, including continuous integration/continuous, deployment (CI/CD) for ML, model versioning, monitoring, and retraining, Proficiency with Scripting and programming languages (Python, R, SQL, etc.), Experience with containerization (Docker) and orchestration (Kubernetes) for ML models, Knowledge of data engineering.
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MLOPS Engineer employer: iBSC
Contact Detail:
iBSC Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOPS Engineer
✨Tip Number 1
Familiarise yourself with Azure services, especially Azure Machine Learning and Azure Kubernetes Service. Consider building a small project or contributing to open-source projects that utilise these technologies to showcase your hands-on experience.
✨Tip Number 2
Network with professionals in the MLOps field through platforms like LinkedIn. Join relevant groups and participate in discussions to increase your visibility and learn about potential job openings directly from industry insiders.
✨Tip Number 3
Stay updated on the latest trends and best practices in MLOps by following blogs, attending webinars, and participating in workshops. This knowledge can help you stand out during interviews and demonstrate your commitment to the field.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and MLOps scenarios. Use platforms like LeetCode or HackerRank to sharpen your skills in Python, R, and SQL, as well as your understanding of CI/CD processes for machine learning.
We think you need these skills to ace MLOPS Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure-based architecture and MLOps. Include specific projects where you've used Azure Machine Learning, AKS, or any relevant machine learning frameworks like TensorFlow or PyTorch.
Craft a Strong Cover Letter: In your cover letter, emphasise your understanding of MLOps concepts and your hands-on experience with CI/CD for ML. Mention how your skills align with the requirements of the consultancy and express your enthusiasm for the role.
Showcase Relevant Projects: If you have worked on projects involving containerization with Docker or orchestration with Kubernetes, be sure to include these in your application. Detail your role and the impact of your contributions.
Highlight Soft Skills: Consultancies often look for candidates who can communicate effectively and work well in teams. Make sure to mention any experiences that demonstrate your collaboration and problem-solving skills, especially in a fast-paced environment.
How to prepare for a job interview at iBSC
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Azure services in detail. Highlight specific projects where you've used Azure Machine Learning, AKS, or Data Lake, and be ready to explain how you implemented MLOps practices.
✨Demonstrate Your Understanding of MLOps
Make sure you can articulate the key concepts of MLOps, such as CI/CD for machine learning. Prepare examples of how you've applied these concepts in previous roles, focusing on model versioning and monitoring.
✨Prepare for Technical Questions
Expect technical questions related to machine learning frameworks like TensorFlow or PyTorch. Brush up on your knowledge of these tools and be ready to discuss how you've used them in real-world applications.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your interest in the company's projects and culture. Inquire about their current MLOps practices or future plans for AI initiatives to demonstrate your enthusiasm for the role.
