Senior MLOps Engineer

Senior MLOps Engineer – Behavioural AI

Build the systems behind next-generation AI authentication

Our global client is building advanced behavioural intelligence technology that enables secure, adaptive digital identity . By analysing how people naturally interact with devices, their AI systems generate powerful authentication signals designed for real-world use at scale.

Our client is moving from R&D into live customer deployments and we’re looking for an experienced Senior MLOps Engineer to help take their behavioural AI models into production and keep them running reliably at scale.

This is a hands-on, high-impact role at the intersection of machine learning and infrastructure.

You’ll own how our models are trained, deployed, monitored, and scaled as real users start relying on them for authentication.

What you’ll be doing

• Turning ML models into production-ready, customer-facing services

• Building and owning end-to-end ML pipelines (training → validation → deployment)

• Creating CI/CD pipelines for models, not just code

• Designing low-latency, high-availability inference infrastructure

• Monitoring live models for drift, performance drops, and failures

• Scaling ML systems as pilot customers onboard

• Working closely with AI, data, and software engineers to ship reliably

What we’re looking for

You don’t need to tick every box, but you will have real experience running ML in production.

Core experience:

• 4+ years in MLOps, ML Engineering, or ML-heavy DevOps roles

• Strong Python and hands-on ML framework experience (PyTorch, TensorFlow, etc.)

• Experience deploying and serving ML models in production

• Containerisation and orchestration (Docker, Kubernetes or ECS)

• AWS experience (e.g. ECS, S3, SageMaker, Lambda)

• CI/CD for ML workflows

• Infrastructure as Code

Nice to have:

• Low-latency / real-time ML systems

• Model monitoring & observability (Prometheus, Grafana, Datadog)

• A/B testing or canary deployments for ML models

• Security-sensitive systems (auth, identity, fintech, etc.)

• Startup or scale-up experience

Why join?

• Work on real-time behavioural AI used in authentication

• High ownership, you’ll shape how ML is run across the company for clients

• Direct impact as we move into live customer deployments

• Hybrid working (Manchester-based)

• Join at a pivotal growth moment, not after everything is already decided