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For Companies 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\’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
- 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
- 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!
DevOps Engineer employer: Aveni
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
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!
Showcase Your Projects: Include specific examples of projects where you've deployed machine learning models or worked with tools like Docker and Kubernetes. We love seeing real-world applications of your skills!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're excited about working with us at Aveni and how your background fits into our mission. Keep it genuine and enthusiastic!
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!
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, 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 prepared to discuss your previous experience with machine learning workflows and how you've automated processes in production environments. Highlight any specific projects where you deployed LLMs or worked with CI/CD pipelines, as this will show your hands-on expertise.
✨Prepare for Collaboration Questions
Since the role involves working closely with engineers and data scientists, think of examples that showcase your teamwork skills. Be ready to explain how you’ve collaborated on projects, resolved conflicts, or contributed to a team’s success in past roles.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and its mission. Inquire about their approach to deploying AI solutions in financial services or how they ensure compliance and security in their models. This demonstrates your enthusiasm and helps you gauge if it’s the right fit for you.
