MLOps & AI Engineer Lead
- Design, implement, and manage scalable and secure infrastructure to support AI/ML workloads
- Build and maintain robust pipelines for model training, validation, deployment, and monitoring
- Act as a trusted technical advisor, understanding client challenges and designing tailored MLOps solutions
- Collaborate with internal teams and clients to translate business needs into practical, scalable AI solutions
- Optimise the performance and reliability of models running in production environments
- Develop and maintain strong client relationships through effective communication and delivery excellence
- Lead technical discovery sessions to identify requirements and key pain points
- Mentor and guide cross-functional teams of ML engineers, data scientists, and consultants, fostering innovation and best practices
- Contribute to the company's thought leadership by participating in industry events and producing content on emerging trends
- Stay ahead of developments in MLOps, DevOps, and AI infrastructure, bringing fresh insights into our work
- Identify skills gaps and support continuous learning through targeted training and development initiatives
- Deep technical expertise in deploying, monitoring, and managing AI/ML solutions in production environments
- Excellent communicator, comfortable working directly with clients and multidisciplinary teams
- Hands-on experience with MLOps tools such as MLflow, DVC, Kubeflow, Docker/Kubernetes, and GitOps practices
- Strong working knowledge of Azure and Databricks services
- Proficient with observability and monitoring tools (e.g. Prometheus, Grafana, Datadog)
- Curious and commercially minded - focused on delivering scalable, valuable solutions
- Familiarity with additional cloud platforms such as AWS or GCP is a plus
- Demonstrated leadership skills, with experience mentoring others and leading delivery efforts
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