Senior Machine Learning Engineer (Full-Stack / GenAI)

Cpl; Galway; Hybrid; EUR 88,000 - 115,000; Full time

Job summary

Cpl in Galway is seeking a Senior Machine Learning Engineer to join a 12-month contract on a hybrid basis. You will integrate ML and GenAI capabilities into scalable, production-grade applications, building end-to-end systems across front-ends, back-ends, APIs and ML-powered services.

The role targets an engineer with 10+ years of software experience and 4–6 years in ML/GenAI in production, with strong Python, AWS, React/Next.js, Node.js, and experience with RAG pipelines, vector databases and

Qualifications

• Education: Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
• Core Experience: 10+ years of professional software engineering (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: 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).
• DevOps & Rigour: 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.

Responsibilities

• Build end-to-end ML-powered production systems.
• Transform prototypes and RAG pipelines into robust enterprise services.
• Collaborate with ML researchers, data scientists, and platform teams.
• Design scalable, secure cloud architectures and APIs.

Skills

End-to-End Engineering

Productising ML

System Design

Observability Engineering

Collaboration

Education

Bachelor’s or Master’s in Computer Science, Engineering, or related field

Tools

Prometheus

Grafana

OpenTelemetry

Docker

Kubernetes

GitHub Actions

IaC

Job description

• 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.