Machine Learning Software Development Engineer (AI)

TL;DR

Machine Learning Software Development Engineer (AI Ops): Designing and deploying production-ready systems combining traditional ML with modern agentic architectures to automate hirify.global's global supply chain with an accent on LLM integration and MLOps. Focus on building autonomous AI agents, developing scalable data pipelines, and creating internal tools for operational automation.

Location: Onsite in Dublin, Ireland

Company

hirify.global is a global leader in e-commerce and cloud computing, currently transforming its operations and supply chain into an AI-native organization.

What you will do

• Build and deploy full-stack ML/LLM-powered features, from data pipelines and model serving to internal user tools.
• Implement AI agent components to automate complex operational workflows across multiple systems.
• Develop internal frontend applications and dashboards to make AI outputs accessible to non-technical users.
• Build integrations across internal APIs, databases, and MCP servers for multi-system orchestration.
• Manage the ML lifecycle, including experimentation, deployment, monitoring, and evaluation.
• Implement guardrails, evaluation frameworks, and human-in-the-loop patterns for production AI systems.

Requirements

• Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related quantitative field.
• Professional software development experience (non-internship).
• Proven experience in machine learning, data mining, NLP, or statistics.
• Experience designing and architecting scalable and reliable systems.
• Proficiency in at least one software programming language.

Nice to have

• Experience with vLLM, SGLang, TensorRT, or similar production platforms.
• Knowledge of AWS services such as S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2.
• Experience in operations or supply chain domains.
• Background in deep learning or computer vision.

Culture & Benefits

• Dynamic environment combining the agility of a startup with the scale of hirify.global Operations.
• Iterative build-measure-learn cycle focused on measurable impact on customer experience.
• High degree of ownership and opportunity to solve highly ambiguous problems.
• Inclusive culture with a strong commitment to diversity and equal opportunity.