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For Companies At a Glance
- Tasks: Design, deploy, and scale cloud solutions while implementing CI/CD pipelines.
- Company: Join a data-driven retail tech start-up making waves in the industry!
- Benefits: Enjoy a hybrid work model with a competitive salary of £80,000 - £95,000.
- Why this job: Be at the forefront of innovation in MLOps and collaborate with cutting-edge technology.
- Qualifications: MSc in a numerical field preferred; MLOps experience required.
- Other info: Experience with computer vision is a plus!
The predicted salary is between 64000 - 84000 £ per year.
MLOPS ENGINEER
LONDON – HYBRID
£80,000 – £95,000
This is a great opportunity for an MLOps engineer from a DevOps background with ML experience to drive cutting-edge work at a data-driven retail tech start-up!
ROLE:
In this role you will:
- Design, deploy and scale on their cloud platform (AWS/GCP)
- Implement and maintain CI/CD pipelines
- Engineering data working closely with the Computer Vision team
- Deploying APIs and packages
- Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value.
- Tech stack: Python, AWS/GCP, Docker, CI/CD, Deep Learning, Kubernetes, DevOps
REQUIREMENTS:
- MSc in a numerical or relevant field is preferred
- MLOps experience is required
- An excellent understanding of DevOps processes and techniques
- Happy working in a fast-paced environment
- Any experience working with computer vision engineers is a bonus!
How To Apply
Please register your interest for this role by sending your CV to Joseph Gregory via the apply link on this page.
MLOps Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer
✨Tip Number 1
Familiarize yourself with the specific cloud platforms mentioned in the job description, like AWS and GCP. Having hands-on experience or projects that showcase your skills in deploying and scaling applications on these platforms will make you stand out.
✨Tip Number 2
Since the role emphasizes CI/CD pipelines, consider contributing to open-source projects or creating your own projects that demonstrate your ability to implement and maintain these pipelines. This practical experience can be a great conversation starter during interviews.
✨Tip Number 3
Stay updated on the latest trends in MLOps and DevOps by following relevant blogs, attending webinars, or joining online communities. Being able to discuss recent advancements or tools can show your passion and commitment to the field.
✨Tip Number 4
If you have any experience working with computer vision engineers, make sure to highlight it in your discussions. Even if it's limited, showing your willingness to collaborate and learn from others in this area can be a significant advantage.
We think you need these skills to ace MLOps Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your MLOps and DevOps experience. Focus on relevant projects, especially those involving cloud platforms like AWS or GCP, and any work with CI/CD pipelines.
Showcase Technical Skills: Emphasize your proficiency in Python, Docker, and Kubernetes. Mention any specific projects where you implemented these technologies, particularly in a data-driven environment.
Highlight Relevant Experience: If you have experience working with computer vision teams, be sure to include that in your application. Detail how you collaborated and the impact of your contributions.
Express Enthusiasm for Innovation: In your cover letter or application message, convey your passion for staying updated on emerging technologies and your eagerness to implement innovative solutions that drive business value.
How to prepare for a job interview at Harnham
✨Showcase Your MLOps Experience
Be prepared to discuss your previous MLOps projects in detail. Highlight specific challenges you faced and how you overcame them, especially in relation to CI/CD pipelines and cloud platforms like AWS or GCP.
✨Demonstrate Your DevOps Knowledge
Since a strong DevOps background is essential for this role, make sure to articulate your understanding of DevOps processes and techniques. Discuss any tools you've used, such as Docker or Kubernetes, and how they contributed to your projects.
✨Stay Updated on Emerging Technologies
Research the latest trends and best practices in MLOps and DevOps. Be ready to share your insights on how these innovations can drive business value, particularly in the context of a data-driven retail tech start-up.
✨Collaborate with Computer Vision Teams
If you have experience working with computer vision engineers, be sure to mention it. Discuss how you collaborated on projects and the impact of that teamwork on the overall success of the initiatives.
