Senior Machine Learning Engineer - AI / GenAI
Core
Design, build, deploy, and support enterprise-scale production-grade Machine Learning, AI, and Generative AI solutions, focusing on operationalization, scaling, and monitoring.
Role type
Senior IC Machine Learning Engineer (GenAI/MLOps)
Builds
Production ML models, GenAI applications, AI agents, RAG solutions, and reusable ML platforms
Domain
Enterprise AI/ML, Cloud-native infrastructure
Deliverable
production ML models
Required skills
Python, SQL, Databricks, MLflow, Kubernetes, Docker, CI/CD, MLOps, Large Language Models, Retrieval-Augmented Generation, AI Agents, Spark, REST API development, Microservices, Model Monitoring
Preferred skills
Azure certifications, Databricks certifications, Kubernetes certifications, DevOps/MLOps certifications
Technologies
Databricks, Azure Kubernetes Service, MLflow, Mosaic AI, Docker, Kubernetes, Spark
Responsibilities
Design and build production-grade ML and AI solutions; Productionise ML models and Data Science pipelines using Databricks; Develop and deploy Generative AI applications, AI agents, and RAG solutions; Build reusable ML pipelines and frameworks using MLOps principles; Implement CI/CD, automated testing, model monitoring, and governance; Deploy and optimise open-source ML and LLMs within AKS; Develop and support REST APIs and microservices; Build scalable containerised solutions using Docker and Kubernetes; Monitor models for performance degradation and drift; Troubleshoot production issues across models, pipelines, and infrastructure; Optimise AI/ML platforms for performance, scalability, and cost efficiency; Mentor junior engineers.
Seniority
Senior, hands-on IC
