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- Tasks: Design and deploy cutting-edge AI/ML systems in a fast-paced environment.
- Company: Join a billion-dollar insurance company revolutionising pet coverage with innovative tech.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Lead the charge in AI/ML deployment and make a real impact on the industry.
- Qualifications: Experience with Google Cloud Platform and building scalable AI/ML workflows.
- Other info: Dynamic team culture 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 City of 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 City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in MLOps. Attend meetups or webinars related to AI and Machine Learning; you never know who might be looking for someone just like you!
✨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 give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on common MLOps scenarios. Be ready to discuss how you've tackled challenges in deploying models and maintaining pipelines. We want to see your problem-solving skills in action!
✨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 take that extra step to connect with us directly.
We think you need these skills to ace MLOps Engineer in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI and Machine Learning workflows, especially on Google Cloud Platform. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about MLOps and how you can contribute to our evolving strategy. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills: Don’t forget to mention your experience with CI/CD pipelines and cloud infrastructure. We’re looking for someone who can hit the ground running, so highlight any tools or frameworks you’ve used that are relevant to the job.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Harvey Nash Group
✨Know Your Tech Stack
Make sure you’re well-versed in the 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 the interview.
✨Showcase Your Projects
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 you stand out!
✨Understand MLOps Best Practices
Familiarise yourself with MLOps strategies, including model monitoring and retraining pipelines. Be prepared to discuss how you’ve implemented best practices in previous roles and how you can contribute to their evolving MLOps strategy.
✨Collaborate and Communicate
Since collaboration is key in this role, think of examples where you’ve worked closely with Product Managers, Engineers, and Data Engineers. Highlight your communication skills and how you’ve supported the integration of models into robust data pipelines.
