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.
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 are 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 would love to hear from you!
What You’ll Be Doing:
- Automating Machine Learning workflows (training → deployment) with AWS & GitOps
- Deploying LLMs using Kubernetes & Docker
- 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
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 are 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 are passionate about leveraging technology to drive positive change and want to be part of a team that is shaping the future of financial services, we would love to hear from you. We know that some people are likely to only apply where they meet 100% of requirements, but we would like to hear from you anyway. Apply now to join us on our mission to transform the financial services industry through AI!
DevOps Engineer in Warrington employer: Aveni
Contact Detail:
Aveni Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land DevOps Engineer in Warrington
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with Aveni employees on LinkedIn. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a GitHub repo showcasing your DevOps projects or contributions to MLOps. This gives us a real taste of what you can do beyond the written application.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of AWS, Docker, and Kubernetes. We want to see how you think on your feet, so practice explaining your past projects and decisions.
✨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 are eager to join our mission.
We think you need these skills to ace DevOps Engineer in Warrington
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the DevOps Engineer role. Highlight your experience with AWS, Docker, Kubernetes, and any MLOps projects you've worked on. We want to see how you can contribute to our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and financial services, and explain why you're excited about working with us at Aveni. Let us know how your background aligns with our goals and values.
Showcase Your Projects: If you've worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to mention them. We love seeing practical examples of your skills, especially in automating ML workflows and deploying models.
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’re considered for the role. Plus, it shows your enthusiasm for joining our team!
How to prepare for a job interview at Aveni
✨Know Your Tech Stack
Make sure you’re familiar with the tools mentioned in the job description, like AWS, Docker, Kubernetes, and Terraform. Brush up on your scripting skills in Python or Bash, as you might be asked to demonstrate your knowledge during the interview.
✨Showcase Your MLOps Experience
Be ready to discuss any hands-on experience you have with machine learning workflows and CI/CD pipelines. Prepare examples of how you've automated processes or deployed models in production environments, especially if you've worked with LLMs.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of the ML lifecycle, model monitoring, and versioning. Practise explaining complex concepts in simple terms, as you may need to collaborate with engineers and data scientists who might not have a deep technical background.
✨Cultural Fit Matters
Aveni values diversity and innovation, so be prepared to discuss how you can contribute to their inclusive culture. Share your passion for financial services and how you see technology driving positive change in the industry.