DevOps Engineer

DevOps Engineer

Full-Time 28800 - 48000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Automate ML workflows and deploy cutting-edge models in production environments.
  • Company: Join Aveni, a leader in AI for financial services with a collaborative culture.
  • Benefits: 34 days holiday, share options, remote work, and continuous learning opportunities.
  • Why this job: Make a real impact in the financial sector using innovative AI technologies.
  • Qualifications: Experience in DevOps or MLOps, with skills in Docker, Kubernetes, and Python.
  • Other info: Diverse and inclusive workplace focused on innovation and career growth.

The predicted salary is between 28800 - 48000 £ per year.

This range is provided by Aveni. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from Aveni

Helping tech, data and analytical focused businesses to scale

Do you want to work on real-world deployments of cutting‑edge machine learning models, including Large Language Models (LLMs)?

Aveni is redefining how AI works for financial services. Our purpose‑built, vertically integrated platform combines proprietary Language Models (FinLLM), intelligent AI Agents, and targeted solutions like Aveni Assist and Aveni Detect. We partner with leading financial institutions to deliver scalable, secure, and compliant AI‑powered solutions that create measurable value across advice, compliance, and operations.

We’re looking for a motivated DevOps Engineer, eager to help us deploy and maintain machine learning models, especially Large Language Models (LLMs), in production environments. If you have solid DevOps experience and are keen to grow your MLOps skills, we’d love to hear from you!

What You\’ll Be Doing:

  • Automating Machine Learning workflows (training → deployment) with AWS & GitOps
  • Building infrastructure with Terraform & Helm
  • Monitoring and maintaining ML models with performance alerts and dashboards
  • Supporting CI/CD for ML pipelines
  • Developing production‑grade APIs (REST/gRPC) to serve models
  • Collaborating with engineers, data scientists & DevOps teams

Your Experience:

  • Industry experience in DevOps or MLOps roles (ideally in AWS environments)
  • Hands‑on with Docker, Kubernetes, and Terraform
  • Strong scripting skills in Python or Bash
  • Familiar with ML lifecycle tools, model monitoring, and versioning
  • Exposure to tools like KServe, Ray Serve, Triton, or vLLM a big plus

Bonus Points:

  • Experience with observability frameworks like Prometheus or OpenTelemetry
  • Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace
  • Exposure to Azure or GCP
  • Passion for financial services

Requirements:

  • Degree in Computer Science, Engineering, Data Science or similar

What We Offer

  • A collaborative and innovative work environment with awesome career growth opportunities
  • 34 days holiday plus your birthday off (inclusive of bank holidays)
  • Share options – we believe in shared success
  • Skills development – continuous learning is at our core, expect the development to be front and centre of everything you do
  • Remote and flexible working – remote, co‑working spaces, or a mix of both
  • Life insurance, income protection and private health care
  • Freebies and discounts at a range of retailers
  • Emotional wellbeing (Employee assistance programme provides access to 24/7 employee counselling and emotional support)
  • Cycle to work scheme
  • Pension scheme (employer contribution matched up to 5%)

Join Us in Making a Difference

At Aveni, we believe that diversity drives innovation. We\’re committed to building a team that reflects the diverse communities we serve and creating an inclusive workplace where everyone feels valued and empowered to contribute their best work. If you\’re passionate about leveraging technology to drive positive change and want to be part of a team that\’s shaping the future of financial services, we\’d love to hear from you. We know that some people are likely to only apply where they meet 100% of requirements, but we’d like to hear from you anyway. Apply now to join us on our mission to transform the financial services industry through AI!

Seniority level

Associate

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Software Development

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Location: London, England, United Kingdom | Salary: $130,000.00-$180,000.00 | Posted: 2 months ago

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DevOps Engineer employer: Aveni

Aveni is an exceptional employer that fosters a collaborative and innovative work culture, perfect for a DevOps Engineer eager to advance their MLOps skills while working on cutting-edge AI solutions for financial services. With generous benefits including 34 days of holiday, share options, and a strong focus on continuous learning and employee wellbeing, Aveni provides a supportive environment where diversity drives innovation and every team member can thrive. Join us in making a meaningful impact in the financial sector while enjoying flexible working arrangements and excellent career growth opportunities.
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Contact Detail:

Aveni Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land DevOps Engineer

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 AWS, Docker, and Kubernetes. This gives potential employers a taste of what you can do and sets you apart from the crowd.

✨Tip Number 3

Prepare for technical interviews by brushing up on your scripting skills and understanding the ML lifecycle. Practice common DevOps scenarios and be ready to discuss how you've tackled challenges in past roles.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who want to make a difference in financial services.

We think you need these skills to ace DevOps Engineer

DevOps
MLOps
AWS
Docker
Kubernetes
Terraform
GitOps
Python
Bash
CI/CD
REST APIs
gRPC
Model Monitoring
Versioning
Observability Frameworks

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your DevOps experience and any MLOps skills you have. Use keywords from the job description to show we’re on the same page!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI in financial services and how your skills can help us deploy cutting-edge models.

Showcase Relevant Projects: If you've worked on projects involving AWS, Docker, or Kubernetes, mention them! We love seeing real-world examples of your work that align with what we do.

Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you don’t miss out on any updates.

How to prepare for a job interview at Aveni

✨Know Your Tech Stack

Make sure you’re well-versed in the technologies mentioned in the job description, like AWS, Docker, and Kubernetes. Brush up on your Terraform skills too! Being able to discuss how you've used these tools in past projects will show that you're ready to hit the ground running.

✨Showcase Your MLOps Knowledge

Since this role focuses on deploying machine learning models, be prepared to talk about your experience with ML workflows. Discuss any specific projects where you automated processes or monitored model performance. This will demonstrate your understanding of the ML lifecycle and your ability to contribute effectively.

✨Prepare for Collaboration Questions

Collaboration is key in this role, so think of examples where you’ve worked closely with engineers or data scientists. Be ready to explain how you communicated technical concepts to non-technical team members, as this shows your ability to work in a diverse team environment.

✨Ask Insightful Questions

At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the tools they use for monitoring ML models, or how they approach CI/CD for ML pipelines. This not only shows your interest but also helps you gauge if the company is the right fit for you.

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