Senior Ml Ops Engineer (Ai)

TL;DR

Senior ML Ops Engineer (AI): Building the operational infrastructure to bring AI and ML models into production at hirify.global:IQ with an accent on cloud infrastructure, ML lifecycle management, and production monitoring. Focus on creating robust, scalable, and maintainable MLOps workflows.

Location: Holborn - London

Company

hirify.global is one of the world’s leading media and entertainment groups, reaching over 50 million individuals across the UK every week.

What you will do

• Design, build, and maintain automated pipelines for model training, validation, packaging, and deployment.
• Implement model registries, experiment tracking, and versioning systems.
• Implement comprehensive monitoring for ML workloads, including prediction latency, throughput, and error rates.
• Establish governance controls for model lineage, approval workflows, reproducibility, and audit trails.
• Partner closely with Data Scientists and ML Engineers to understand requirements and translate experimental work into production-ready systems.

Requirements

• Strong programming skills (Python preferred) with a focus on production-quality, testable, and maintainable code.
• Hands-on MLOps experience operationalizing ML models in production.
• Cloud platform expertise (AWS strongly preferred; Snowflake a plus).
• Experience with MLOps tooling such as MLflow, Weights & Biases, SageMaker Model Registry, Airflow, Prefect, Step Functions.
• Deep understanding of monitoring and observability for ML systems.
• Experience with ML-specific CI/CD patterns, Terraform, and containerisation (Docker).

Nice to have

• Experience with agentic and AI-accelerated coding tools.
• Understanding of ML model types and performance characteristics.
• Familiarity with advertising technology, marketing analytics, or media measurement use cases.
• Experience in early-stage or scale-up environments.
• Knowledge of data governance, privacy, and compliance requirements in data-driven products.

Culture & Benefits

• Inclusive culture that values diversity.
• Commitment to making appropriate adjustments to the recruitment process and workplace to be fully inclusive to people with different needs and working styles.