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For Companies At a Glance
- Tasks: Lead the deployment of AI/ML models and ensure cloud infrastructure reliability.
- Company: Join Code and Theory, a digital-first creative agency at the tech-creative intersection.
- Benefits: Competitive salary, remote work options, and opportunities for professional growth.
- Why this job: Make a real impact on innovative projects with top-tier clients like TikTok and Amazon.
- Qualifications: Experience in MLOps, cloud deployment, and strong programming skills in Python.
- Other info: Be part of a diverse team of nearly 2,000 talented individuals across the globe.
The predicted salary is between 48000 - 72000 £ per year.
We are seeking an experienced Lead ML+DevOps Engineer. The ideal candidate will have strong expertise in cloud deployment, containerization, and related technologies, and will play a crucial role in the scalability and reliability of our AI/ML infrastructure.
WHAT YOU'LL NEED
- Extensive experience in deploying machine learning models to cloud environments
- Strong expertise in Docker container orchestration
- Proficiency in Terraform for infrastructure as code (IaC) and cloud resource management
- Hands-on experience with streaming data platforms (e.g., Kafka, Kinesis)
- Solid understanding of data cleaning, transformation, and ETL processes
- Experience with CI/CD tools and pipelines (e.g., Jenkins, GitLab CI)
- Strong programming skills in Python. Familiarity with ML frameworks (e.g., TensorFlow, PyTorch) is a plus
- Excellent problem-solving skills and the ability to think critically and creatively
- Strong communication skills with the ability to convey technical concepts to non-technical stakeholders
Lead Engineer, MLOps (London) employer: Code and Theory
Contact Detail:
Code and Theory Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Engineer, MLOps (London)
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving cloud deployment and container orchestration. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to tackle technical questions and case studies that demonstrate your expertise in MLOps. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with tools like Docker and Terraform, and let your passion shine through!
We think you need these skills to ace Lead Engineer, MLOps (London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with cloud deployment and containerization. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in Docker and Terraform!
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 your problem-solving skills can contribute to our team. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any cool projects involving machine learning models or CI/CD pipelines, make sure to mention them! We love seeing real-world applications of your skills, especially if they relate to streaming data platforms.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Code and Theory
✨Know Your Tech Inside Out
Make sure you brush up on your cloud deployment and container orchestration skills. Be ready to discuss your experience with Docker and Terraform, as well as any streaming data platforms you've worked with. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to share instances where you've tackled complex problems in your previous roles. Think about how you approached challenges related to AI/ML infrastructure and be ready to explain your thought process clearly.
✨Communicate Like a Pro
Since you'll need to convey technical concepts to non-technical stakeholders, practice explaining your work in simple terms. This will demonstrate your strong communication skills and ability to bridge the gap between tech and business.
✨Familiarise Yourself with CI/CD Tools
Get comfortable discussing your experience with CI/CD tools like Jenkins or GitLab CI. Be prepared to talk about how you've implemented these in your projects and the impact they had on your workflow.
