Senior Machine Learning Engineer (Full-Stack / GenAI)
- Location: Galway, Ireland (Hybrid options available)
- Job Type: 12-Month Contract
- Daily Rate: €550 per day
About the Role
We are seeking a Senior Machine Learning Engineer with exceptional software engineering fundamentals to join our team in Galway. In this role, you will seamlessly integrate Machine Learning and GenAI capabilities into scalable, production-grade applications.
This position is ideal for an experienced engineer (10+ years) who thrives on building end-to-end systems—including front-ends, back-ends, APIs, and ML-powered services—rather than academic research. You will partner closely with ML researchers, data scientists, and platform teams to transform prototypes, RAG pipelines, and agentic workflows into robust enterprise systems.
The Expertise We’re Looking For
- Education: Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field.
- Core Experience: 10+ years of professional software engineering experience (full-stack, distributed systems, APIs, cloud).
- ML/GenAI Focus: 4–6 years of experience working with machine learning or GenAI systems in production.
- AI Frameworks: Hands-on experience designing and deploying RAG pipelines, embeddings, vector search, and agentic frameworks (e.g., LangChain, CrewAI, LangGraph, AutoGen).
- Vector Databases: Proficiency with FAISS, Pinecone, Weaviate, or Milvus.
- Cloud Architecture: Strong expertise in cloud-native engineering, specifically AWS (S3, Lambda, ECS/EKS, SageMaker, API Gateway).
- Development Stack: Advanced Python paired with modern front-end frameworks (React/Next.js, Angular) and back-end systems (Node.js, Java, C#, or Go).
- Data Systems: Experience with relational databases (Oracle), cloud data warehouses (Snowflake), and knowledge graphs (Neo4j, RDF/SPARQL).
- DevOps & Rigour: Proven experience with CI/CD pipelines, Docker, Kubernetes, GitHub Actions, and Infrastructure as Code (IaC).
- Ethical AI: Strong understanding of Responsible AI, data privacy, and ethical considerations.
- Bonus: Experience with model monitoring, evaluation frameworks, and automated alerting.
The Skills You Bring
- End-to-End Engineering: Ability to build complete full-stack applications that seamlessly integrate ML/GenAI services.
- Productising ML: Highly skilled at converting research notebooks and prototypes into production APIs and scalable microservices.
- System Design: Comfortable managing distributed systems, containerisation, scaling, observability, and resilience.
- Observability Engineering: Experience with Prometheus, Grafana, OpenTelemetry, and logging/metrics pipelines.
- Collaboration: Strong communication skills to articulate architectural decisions and technical concepts to non-technical business partners.
The Value You Deliver
- Build Full-Stack Components: Deliver the APIs, UIs, and services that bring ML and GenAI capabilities directly into core business applications.
- Scalable Platforms: Create secure, reliable platforms for RAG, model serving, and agentic applications.
- Drive Productivity: Improve engineering velocity by creating reusable patterns, libraries, and frameworks for ML integration.
- Cross-Functional Impact: Collaborate closely with ML researchers, product teams, and cloud engineering to deliver measurable enterprise business impact.
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