Founding ML Engineer

Full-time

Dublin, Ireland

€32,000 - €45,000 + equity

About

We’re building an AI platform that delivers intelligent, real-time experiences for digital commerce. Our system combines computer vision and machine learning with scalable infrastructure to power next-generation online interactions.

We’re early-stage, near-MVP, funded, and moving fast. As a founding ML engineer, you’ll design core systems, shape the technical culture, and help deliver the product to our first customers. We move with a San Francisco startup mindset: rapid iteration, full ownership, and building for scale.

What You'll Build

Applied ML Systems

• Train, adapt, and deploy deep learning models in production
• Build scalable inference pipelines for image, video, and data processing
• Integrate in-house models with external AI services

Data & Infrastructure

• Event-driven pipelines using AWS (SageMaker, Lambda, SQS, DynamoDB, S3)
• Auto-scaling ML workloads with monitoring and cost efficiency
• CI/CD pipelines and observability for ML deployments

End-to-End Ownership

• Data preprocessing and feature pipelines
• Model serving, inference optimization, and integration with product features
• Performance tuning across ML, backend, and infrastructure layers

Key Responsibilities

• Design and deploy ML models for production use cases
• Build robust, scalable inference pipelines across multiple data types
• Own the lifecycle of ML models, from research to customer-facing deployment
• Work closely with full-stack engineers to bring ML capabilities into the product
• Define experimentation, monitoring, and retraining practices for production ML
• Partner with founders to shape product direction and iterate quickly

Required Skills

Core ML Expertise

• 2+ years experience applying ML in production
• Proficiency with PyTorch, TensorFlow, Hugging Face, or similar frameworks
• Knowledge of inference optimization and model deployment

Software Engineering

• Strong backend development (Python)
• Experience with databases (SQL & NoSQL, DynamoDB a plus)
• Familiarity with distributed systems and APIs

Cloud & Infrastructure

• AWS: SageMaker, Lambda, API Gateway, S3, DynamoDB, CloudFront, SQS
• Real-time and event-driven system design

Startup Mindset

• Comfortable with ambiguity and rapid iteration
• Ownership from prototype to production
• Excited to apply AI/ML to complex, real-world problems

Nice-to-Have

• GPU optimization
• Multi-tenant SaaS architecture
• Computer vision OpenCV
• Performance optimization: caching, bundle size, CDN configuration
• AI & startup excitement: work with cutting-edge models, ship weekly features, solve complex full-stack challenges

Why Join

• Foundational impact: architect core systems, define technical culture, influence product roadmap
• Founding-level compensation: equity stake with competitive base salary
• Direct business impact: build features that drive customer acquisition, retention, and revenue
• AI & startup excitement: work with cutting-edge models, ship weekly features, solve complex full-stack challenges