Senior Machine Learning Engineer (Full-Stack / GenAI)

Cpl; Galway; Híbrido; EUR 20.295.000 - 23.247.000; Jornada completa

Descripción de la vacante

Cpl in Galway seeks a Senior Machine Learning Engineer to embed ML and GenAI into scalable, production-grade apps. You will join a team partnering with ML researchers, data scientists, and platform teams to transform prototypes into enterprise-grade workflows.

The role emphasizes end-to-end engineering across front-ends, back-ends, APIs, and ML-powered services, with a strong focus on responsible AI and scalable architectures.

Formación

• 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 working with ML/GenAI systems in production.
• AI Frameworks: Experience designing/deploying RAG pipelines, embeddings, vector search, and agentic frameworks.
• Vector Databases: Proficiency with FAISS, Pinecone, Weaviate, or Milvus.
• Cloud Architecture: Strong AWS expertise (S3, Lambda, ECS/EKS, SageMaker, API Gateway).
• Development Stack: Advanced Python with React/Next.js/Angular and back-end (Node.js/Java/ C#/Go).
• Data Systems: Relational DBs (Oracle), Snowflake, knowledge graphs (Neo4j, RDF/SPARQL).
• DevOps & Rigour: CI/CD, Docker, Kubernetes, GitHub Actions, IaC.
• Ethical AI: Responsible AI, data privacy, and ethics.
• Bonus: Model monitoring and alerting experience.

Responsabilidades

• Build end-to-end full-stack applications integrating ML/GenAI services.
• Productise ML: turn research into production APIs and microservices.
• Design distributed systems with containerisation, scaling, and resilience.
• Work on observability with Prometheus, Grafana, OpenTelemetry.
• Collaborate with ML researchers, product teams, and cloud engineers.

Conocimientos

End-to-End Engineering

Productising ML

System Design

Observability Engineering

Collaboration

CI/CD

Docker & Kubernetes

Educación

Bachelor’s or Master’s in CS/Engineering

Herramientas

LangChain

CrewAI

LangGraph

AutoGen

FAISS

Pinecone

Weaviate

Milvus

AWS

SageMaker

React/Next.js/Angular

Node.js/Java/C#/Go

Descripción del empleo

• Location: Galway, Ireland (Hybrid options available)
• Job Type: 12-Month Contract
• Daily Rate: €550 per day

• 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.