MLOps Engineer: Pipelines, AWS & Edge Deployments

MLOps Engineer: Pipelines, AWS & Edge Deployments

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
Enigma

At a Glance

  • Tasks: Own and optimise ML pipelines and infrastructure for a clinical monitoring platform.
  • Company: Enigma, a forward-thinking tech company in London.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Join a dynamic team dedicated to innovation and impactful solutions.
  • Why this job: Make a real difference in healthcare by enhancing patient outcomes with cutting-edge ML technology.
  • Qualifications: Experience in MLOps, cloud environments, and strong collaboration skills.

The predicted salary is between 63000 - 77000 £ per year.

Enigma in London is seeking an experienced MLOps Engineer to own the infrastructure and lifecycle of production ML systems powering a clinical monitoring platform. You will build and maintain production ML pipelines, deployment infrastructure, and monitoring to support predictive models and patient outcomes.

You will collaborate with ML, backend, data, and clinical teams to ensure models are trained, versioned, deployed, and monitored across cloud and edge environments.

MLOps Engineer: Pipelines, AWS & Edge Deployments employer: Enigma

Enigma is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong focus on employee growth, we provide ample opportunities for professional development and hands-on experience in cutting-edge technologies within the healthcare sector. Our commitment to reliability, security, and privacy compliance ensures that you will be part of a meaningful mission, making a real impact on clinical monitoring and patient care.

Enigma

Contact Details:

Enigma Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land MLOps Engineer: Pipelines, AWS & Edge Deployments

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Enigma or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Enigma.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Enigma.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Enigma that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace MLOps Engineer: Pipelines, AWS & Edge Deployments

MLOps
Production ML Systems
ML Pipelines
Deployment Infrastructure
Monitoring
Predictive Models
Collaboration

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Enigma.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Enigma and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Enigma

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Enigma uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.