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For Companies At a Glance
- Tasks: Build APIs and manage ML infrastructure while deploying models into production.
- Company: Join a cutting-edge recruitment firm focused on innovative tech solutions in London.
- Benefits: Enjoy flexible working options and a dynamic work environment with great perks.
- Why this job: Be part of a team that drives impactful machine learning projects and enhances your skills.
- Qualifications: 5+ years of experience in Senior MLOps is required.
- Other info: Opportunity to work with advanced technologies like Kubernetes, Docker, and Terraform.
The predicted salary is between 60000 - 84000 £ per year.
What you’ll do:
- Build and maintain APIs (FastAPI or similar) to serve ML models
- Design and manage robust ML infrastructure using Kubernetes, Docker, and Terraform
- Deploy machine learning models into production environments
Responsibilities:
- Collaborate with ML teams to streamline training, deployment, and monitoring.
- Build internal tools and dashboards (e.g., in React or Vue) for analytics and observability.
- Own CI/CD pipelines and drive infrastructure automation.
Requirements:
- 5+ years' experience in Senior ML Ops.
Senior MLops (Full Stack) Engineer | London | Foundation Models in London - SoCode Recruitment employer: Java Script Works
Contact Detail:
Java Script Works Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLops (Full Stack) Engineer | London | Foundation Models in London - SoCode Recruitment
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as FastAPI, Kubernetes, Docker, and Terraform. Having hands-on experience or projects showcasing these skills can significantly boost your chances.
✨Tip Number 2
Network with professionals in the MLOps field, especially those who work with foundation models. Attend relevant meetups or webinars to connect with potential colleagues and learn about industry trends.
✨Tip Number 3
Showcase your ability to collaborate effectively by discussing past experiences where you worked closely with ML teams. Highlight any successful projects that involved streamlining deployment or monitoring processes.
✨Tip Number 4
Prepare to discuss your experience with CI/CD pipelines and infrastructure automation during interviews. Be ready to provide examples of how you've implemented these practices in previous roles to improve efficiency.
We think you need these skills to ace Senior MLops (Full Stack) Engineer | London | Foundation Models in London - SoCode Recruitment
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in MLOps, particularly with technologies like Kubernetes, Docker, and Terraform. Include specific projects where you've built APIs or deployed ML models.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and infrastructure automation. Mention how your skills align with the responsibilities listed in the job description, such as collaborating with ML teams and owning CI/CD pipelines.
Showcase Relevant Projects: If you have worked on relevant projects, consider including a portfolio or links to your work. Highlight any internal tools or dashboards you've built, especially if they involved React or Vue.
Proofread and Edit: Before submitting your application, carefully proofread your documents. Check for any spelling or grammatical errors, and ensure that your formatting is consistent and professional.
How to prepare for a job interview at Java Script Works
✨Showcase Your Technical Skills
Be prepared to discuss your experience with APIs, Kubernetes, Docker, and Terraform. Highlight specific projects where you've successfully deployed ML models and managed infrastructure.
✨Demonstrate Collaboration
Since the role involves working closely with ML teams, share examples of how you've collaborated in the past. Discuss any tools or processes you’ve implemented to improve teamwork and efficiency.
✨Prepare for Problem-Solving Questions
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when faced with challenges in deploying or maintaining ML models.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's ML infrastructure and future projects. This shows your genuine interest in the role and helps you understand if it's the right fit for you.
