DevOps / MLOps Engineer in Edinburgh

About the Role

Are you passionate about building infrastructure that powers AI systems capable of learning from and trading global financial markets in real time? Predictiva is looking for a DevOps / MLOps Engineer to take full ownership of our internal and production infrastructure as we continue to scale. You will work directly with the CTO and engineering teams across our autonomous trading platforms, our AI consulting engagements with financial institutions, and our growing suite of applied AI services. This is a highly practical, high-ownership role. It suits a strong mid-level engineer ready to step up, or a senior engineer who wants broad responsibility in a fast-moving, technically ambitious environment.

About Predictiva

Predictiva is an award-winning AI FinTech company developing autonomous trading systems that leverage advanced machine learning to trade global financial markets. Our mission is to make cutting-edge AI trading technology accessible to professionals and institutions worldwide. Our platforms serve both enterprise clients and a growing retail user base across multiple countries. We also partner with financial institutions across the UK, Europe, and the GCC to deliver applied AI implementations in production environments. Backed by a team of researchers, engineers, and financial experts, Predictiva is recognised as one of the Top 50 Data-Driven AI Startups in Europe and is a winner of the Innovate UK Smart Grant.

Key Responsibilities

• Infrastructure Ownership: Own, improve, and standardise company infrastructure across AWS, Azure, GCP, and on-premises/Proxmox environments. Design and build infrastructure for new trading, ML, and data engineering projects. Manage cloud networking, IAM, security boundaries, secrets, and deployment environments. Contribute to architecture and design decisions across the company's infrastructure estate.
• Containers and Orchestration: Operate and maintain containerised workloads using Docker, Kubernetes, EKS, Azure Container Apps, and Cloud Run.
• Infrastructure as Code and Automation: Maintain and improve infrastructure as code using Terraform and Ansible. Build and support CI/CD workflows using GitHub Actions and ArgoCD.
• Observability and Reliability: Improve monitoring, alerting, logging, and distributed tracing using Prometheus, Grafana, ELK, OpenTelemetry, and cloud-native tools. Drive improvements to infrastructure reliability, cost efficiency, security, and maintainability.
• Data and ML Infrastructure: Support databases, streaming systems, and data infrastructure, including Kafka/MSK, Redis, MongoDB, PostgreSQL/RDS, TSDB, BigQuery, and Bigtable. Support ML model deployment pipelines, experiment tracking, and model lifecycle management.
• Developer Support: Work closely with developers to support deployments, debug environment issues, and resolve operational problems quickly.

About You

We are looking for someone who can contribute quickly, take ownership, and make sound engineering decisions. The ideal candidate has operated real production systems, understands tradeoffs, and can articulate why they chose a particular approach rather than simply listing tools. You should be comfortable in a startup environment where priorities shift quickly and ownership is broad.

Essential qualifications:

• 3+ years of professional experience in DevOps, infrastructure engineering, platform engineering, SRE, or cloud engineering.
• Strong hands-on experience operating production infrastructure.
• Strong Linux administration skills and networking fundamentals.
• Production experience with at least one major cloud provider; ideally across GCP, AWS, and Azure.
• Hands-on experience with Docker and Kubernetes.
• Experience with infrastructure as code, especially Terraform.
• Experience with configuration management and automation, ideally Ansible.
• Experience building and maintaining CI/CD pipelines.
• Experience with monitoring, logging, metrics, tracing, alerting, and incident investigation.
• Practical experience with IAM, secrets management, access control, and infrastructure security.
• Ability to debug complex infrastructure, deployment, and runtime issues.
• Strong scripting ability in Python and shell.
• A BSc or higher in Computer Science, Engineering, or a related technical field.

Desirable qualifications:

• Experience with Ray clusters or distributed ML compute infrastructure.
• Experience with Weights and Biases or equivalent ML experiment tracking platforms.
• MLOps or model lifecycle management experience.
• Familiarity with ML/AI platform infrastructure or RAG-based applied AI systems.
• Experience with trading systems, fintech, or financial market infrastructure.
• Cloud architecture certifications from AWS, Azure, or GCP.
• Cost optimisation experience in multi-cloud environments.
• Developer tooling or internal platform improvement experience.

What We Offer

• Competitive salary.
• Pension scheme.
• Employee share options through our equity pool.
• 28 days paid annual leave plus UK bank holidays.
• Free unlimited personal access to our trading platforms.
• Access to powerful cloud-based compute resources.
• Company laptop and technical tools.
• The opportunity to work on production AI and FinTech infrastructure at a genuine scale.
• A collaborative environment of scientists, engineers, and financial innovators.

Why Join Us

At Predictiva, you will have the chance to work at the intersection of AI research, financial innovation, and scalable infrastructure engineering. You will help build and operate the systems that keep our trading platforms and AI services running reliably at scale, and you will do it alongside a team that values ownership, technical excellence, and pragmatic problem-solving.