Senior ML Platform Engineer

Iterable; Lisboa; Híbrido; EUR 66 500 - 88 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Private Medical Insurance

Meal Allowance: 8.55€ per day

Community Days

Paid Annual Leave (22 days)

Global Lifestyle Reimbursement Account

Resumo da oferta

Iterable is seeking a Senior Machine Learning Engineer to build core ML foundations powering Nova’s agentic experiences. This role focuses on production ML—retrieval pipelines, evaluation frameworks, and model integration layers to ensure reliability, scalability, and repeatability within the platform.

You will partner with backend, frontend, and product teams to integrate ML across the company, drive architectural decisions, and prototype solutions, while maintaining security and observability

Qualificações

• 5+ years of experience in production ML systems.
• Proficient in Python or TypeScript and ML workflows.
• Experience with retrieval systems, vector databases, or RAG architectures.
• Able to lead complex projects in ambiguous environments.

Responsabilidades

• Design and build ML platform components for agentic systems.
• Operationalize RAG use cases across data sourcing and embeddings.
• Develop evaluation frameworks for LLM- and agent-based features.
• Collaborate with backend engineers to productionize ML features.
• Ensure secure handling of data in ML workflows.
• Collaborate with product and design to align ML system design with goals.
• Contribute to iterative improvements of the Nova agent framework with Mastra and TypeScript.

Ferramentas

Mastra

LLM toolkits

Descrição da oferta de emprego

Iterable is seeking a Senior Machine Learning Engineer to build core ML foundations powering Nova’s agentic experiences. This role focuses on production ML—retrieval pipelines, evaluation frameworks, and model integration layers to ensure reliability, scalability, and repeatability within the platform.

You will partner with backend, frontend, and product teams to integrate ML across the company, drive architectural decisions, and prototype solutions, while maintaining security and observability