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 Β£ 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\βre 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\βll Be Doing:
- Automating Machine Learning workflows (training β 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 β we believe in shared success
- Skills development β continuous learning is at our core, expect the development to be front and centre of everything you do
- Remote and flexible working β 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\βre 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\βre passionate about leveraging technology to drive positive change and want to be part of a team that\βs shaping the future of financial services, we\βd 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 π€«
We think this is how you could land DevOps Engineer
β¨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.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your DevOps projects, especially those involving AWS, Docker, and Kubernetes. This gives us a tangible sense of what you can bring to the table.
β¨Tip Number 3
Prepare for the interview by brushing up on your MLOps knowledge. Be ready to discuss how you've automated workflows or deployed models in the past. We love hearing about real-world experiences!
β¨Tip Number 4
Donβt forget to apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, weβre always on the lookout for passionate candidates like you!
We think you need these skills to ace DevOps Engineer
Some tips for your application π«‘
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 weβre on the same page!
Showcase Your Projects: Include specific examples of projects where you've automated workflows or deployed models. We love seeing real-world applications of your skills, especially with AWS, Docker, and Kubernetes.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're excited about working with AI in financial services and how your background makes you a great fit for our team.
Apply Through Our Website: We encourage you to apply directly through our website. Itβs the best way for us to receive your application and ensures you donβt miss out on any important updates!
How to prepare for a job interview at Aveni
β¨Know Your Tech Stack
Make sure youβre 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 these will likely come up during technical discussions.
β¨Showcase Your MLOps Knowledge
Since this role focuses on deploying machine learning models, be prepared to discuss your experience with ML lifecycle tools and model monitoring. Bring examples of how you've automated workflows or supported CI/CD for ML pipelines in past roles.
β¨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills. Think about challenges you've faced in previous DevOps roles and how you overcame them, especially in relation to deploying and maintaining ML models.
β¨Demonstrate Your Passion for Financial Services
Aveni is looking for someone whoβs not just technically skilled but also passionate about financial services. Be ready to discuss why youβre interested in this sector and how you see technology transforming it, particularly through AI.