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- Tasks: Design and deploy cutting-edge AI/ML systems while ensuring best practices.
- Company: Join a billion-dollar insurance company revolutionising pet coverage with innovative tech.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Lead the charge in AI/ML deployment and make a real impact in a fast-growing company.
- Qualifications: Experience with Google Cloud Platform and building scalable AI/ML workflows.
- Other info: Dynamic, agile environment with a focus on collaboration and innovation.
The predicted salary is between 36000 - 60000 £ per year.
Partnered with a global insurance company who specialise in providing market leading and innovative cover for household pets, having achieved remarkable growth and now operating as a Billion Dollar organisation they are scaling their Data Engineering and Analytics practise and keen to bring onboard an experienced MLOps Engineer to spearhead the deployment of AI and Machine Learning models and ensure best practises are adhered across the business.
Scope of role:
- Design, build and deploy AI/Machine Learning systems in production.
- Develop scalable AI/ML Solutions with a focus on model implementation, performance and reliability.
- Take ownership of the End to End AI/ML pipelines through deployment and monitoring.
- Contribute to their evolving MLOps Strategy, including model monitoring, retraining pipelines and enabling best practises.
- Implement and evaluate new tools, frameworks to improve end to end AI/ML lifecycle from concept to production.
- Collaborate extensively with Product Managers, Engineers and Data Engineers supporting the integration of models and ensuring robust data pipelines.
Experience required:
- Experience designing, building and deploying AI / Machine Learning workflows on Google Cloud Platform, in particular Vertex AI.
- Architecting and maintaining CI/CD pipelines that deliver models into production.
- Cloud infrastructure and IAC experience, with Terraform supporting scalable ML systems.
- Strong knowledge of Data Governance, Data lineage and security practises.
- Agile/Kanban setup in a fast-paced scale-up environment.
- Cloud-based GPU model training and online/offline feature stores.
- Full-Stack Data Science background from training and deploying AI/ML models.
If this opportunity aligns with your background and career aspirations please share your details to daniel.neaves@harveynash.com, your latest CV and availability for a call.
MLOps Engineer in London employer: Harvey Nash Group
Contact Detail:
Harvey Nash Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in MLOps. A friendly chat can lead to insider info about job openings or even referrals that could give you a leg up.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those involving Google Cloud Platform and CI/CD pipelines. This will not only impress potential employers but also give you confidence during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of data governance and security practices. Be ready to discuss how you've implemented these in past projects, as this is crucial for the role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace MLOps Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the MLOps Engineer role. Highlight your experience with AI/ML workflows, especially on Google Cloud Platform and Vertex AI. We want to see how your skills align with the job description!
Showcase Your Projects: Include specific projects where you've designed, built, or deployed AI/ML systems. We love seeing real-world examples of your work, especially if they demonstrate your ability to manage end-to-end pipelines and CI/CD processes.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for easy reading and make sure to highlight your key achievements in MLOps. We appreciate straightforward communication!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Harvey Nash Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the tools and technologies mentioned in the job description, especially Google Cloud Platform and Vertex AI. Brush up on your experience with CI/CD pipelines and Terraform, as these will likely come up during technical discussions.
✨Showcase Your MLOps Experience
Prepare to discuss specific projects where you've designed, built, and deployed AI/ML systems. Be ready to explain your role in the end-to-end pipeline and how you ensured model performance and reliability. Real-world examples will make your experience stand out.
✨Understand Their Business
Research the insurance company and their focus on pet coverage. Understanding their market and how AI/ML can enhance their services will show your genuine interest and help you tailor your answers to align with their goals.
✨Collaborative Mindset
Since the role involves working closely with Product Managers and Engineers, be prepared to discuss how you’ve collaborated in past roles. Highlight your communication skills and how you’ve contributed to team success, especially in fast-paced environments.
