DevOps / MLOps Engineer

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. 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.   -----------------------------   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.   -----------------------------   As our DevOps / MLOps Engineer, you will:   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. Improve monitoring, alerting, logging, and distributed tracing using Prometheus, Grafana, ELK, OpenTelemetry, and cloud-native tools. 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. Work closely with developers to support deployments, debug environment issues, and resolve operational problems quickly.   -----------------------------   We are looking for someone who can contribute quickly, take ownership, and make sound engineering decisions. You should be comfortable in a startup environment where priorities shift quickly and ownership is broad.   3+ years of professional experience in DevOps, infrastructure engineering, platform engineering, SRE, or cloud engineering. ~ Strong Linux administration skills and networking fundamentals. ~ ideally across GCP, AWS, and Azure. ~ 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. ~ 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.   Experience with Ray clusters or distributed ML compute infrastructure. Experience with Weights and Biases or equivalent ML experiment tracking platforms. 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. Competitive salary. ~ Pension scheme. ~ 28 days paid annual leave plus UK bank holidays. ~ 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.   -----------------------------   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.