Senior Machine Learning Engineer
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Summary
12-month contract (hybrid in Galway) for a Senior ML Engineer to build production-ready full-stack applications integrating ML and GenAI — RAG pipelines, embeddings/vector search, and agentic workflows using LangChain, LangGraph or CrewAI on AWS. Pays up to €500 per day.
Senior Machine Learning Engineer – GenAI & Full Stack
Location: Galway – Hybrid
Rate: Up to €500 per day
Contract: Initial 12-month contract
We are looking for an experienced Senior Machine Learning Engineer to build scalable, production-ready applications integrating Machine Learning and Generative AI. You will combine strong software engineering and full-stack development skills with hands-on ML/GenAI expertise, turning prototypes, RAG pipelines and agentic workflows into reliable enterprise applications.
Key Responsibilities
Essential Skills & Experience
Desirable: Experience with model evaluation, monitoring and observability tools such as Prometheus, Grafana and OpenTelemetry.
The Ideal Candidate - A hands-on engineer who can bridge software engineering and AI, transforming innovative ML/GenAI concepts into secure, scalable and production-ready business applications.
Location: Galway – Hybrid
Rate: Up to €500 per day
Contract: Initial 12-month contract
We are looking for an experienced Senior Machine Learning Engineer to build scalable, production-ready applications integrating Machine Learning and Generative AI. You will combine strong software engineering and full-stack development skills with hands-on ML/GenAI expertise, turning prototypes, RAG pipelines and agentic workflows into reliable enterprise applications.
Key Responsibilities
- Develop full-stack applications integrating ML and GenAI capabilities.
- Build and deploy RAG pipelines, embeddings and vector search solutions.
- Design scalable APIs, microservices and cloud-native applications.
- Implement agentic workflows using frameworks such as LangChain, LangGraph or CrewAI.
- Develop and deploy solutions using AWS and modern DevOps practices.
- Ensure applications are secure, reliable, scalable and production-ready.
- Implement automated testing, CI/CD, monitoring and observability.
- Evaluate emerging AI technologies and identify opportunities for business adoption.
Essential Skills & Experience
- 10+ years of software engineering experience.
- 4–6 years delivering ML or GenAI solutions in production.
- Advanced Python skills and experience with Java, Node.js, C# or Go.
- Full-stack development experience with React, Next.js, Angular or similar.
- Hands-on experience with RAG pipelines, embeddings and vector databases such as Pinecone, FAISS or Weaviate.
- Experience with agentic frameworks such as LangChain, LangGraph, CrewAI or AutoGen.
- Strong knowledge of AWS, Docker, Kubernetes, CI/CD and distributed systems.
- Understanding of Responsible AI, data privacy and secure development.
- Strong communication and problem-solving skills.
Desirable: Experience with model evaluation, monitoring and observability tools such as Prometheus, Grafana and OpenTelemetry.
The Ideal Candidate - A hands-on engineer who can bridge software engineering and AI, transforming innovative ML/GenAI concepts into secure, scalable and production-ready business applications.