Senior Machine Learning Engineer (Nova)

Iterable; Lisboa; Presencial; EUR 67 000 - 88 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Private Medical Insurance

Life/Risk Assurance

Meal Allowance

Paid Annual Leave

Global Lifestyle Reimbursement

Paid Sabbatical

Complete laptop

Resumo da oferta

Iterable seeks a Senior Machine Learning Engineer to build core ML foundations powering Nova’s agentic experiences. You will design and implement components for retrieval pipelines and model integration in production.

You will work with backend, frontend, and product teams to operationalize RAG use cases, evaluate features, and ensure data security while scaling AI across the platform from Lisbon-based teams.

Qualificações

• 5+ years of experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in Mastra or comparable toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.

Responsabilidades

• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines and model integration layers.
• Introduce and operationalize RAG use cases from data sourcing to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns for ML- and LLM-powered experiences.
• Partner with backend engineers to productionize ML features with reliability, observability, and performance.
• Prototype applied ML solutions to validate feasibility before full builds.
• Ensure secure handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML designs with user goals.
• Contribute to iterative improvements of the Nova agent framework with Mastra and TypeScript.

Conhecimentos

Python

TypeScript

ML pipelines

RAG

Retrieval systems

LLM integration

Distributed systems

Communication skills

Ferramentas

Mastra

Vector databases

LLM toolkits

Descrição da oferta de emprego

Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross-channel interactions, and optimize engagement—all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences.

Our success is powered by extraordinary people who bring our core values—Be an Owner, Growth Mindset, Run as One, Transparency —to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That’s why we’ve been recognized as one of Inc’s Best Workplaces and Fastest Growing Companies, and were recognized on Forbes’ list of America’s Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront’s Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work.

With a global presence—including offices in San Francisco, Denver, London, Sydney, and Lisbon, plus remote employees worldwide—we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let’s shape the future of customer engagement together!

We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova’s agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform.

You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands-on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast-moving, cross-functional product environment.

Position Details:

• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers.
• Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns.
• Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring.
• Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently.
• Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics.
• Prototype applied ML solutions to validate feasibility before investing in full builds.
• Ensure secure, robust handling of data used in ML workflows and retrieval operations.
• Collaborate with product, design, and engineering to align ML system design with user experience and product goals.
• Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.

The Ideal Candidate Will Be/Have:

• 5+ years of experience as a Machine Learning Engineer or similar role focused on production systems.
• Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits.
• Experience with retrieval systems, vector databases, search technologies, or RAG architectures.
• Prior work integrating ML or LLM-powered features into production applications.
• Understanding of ML evaluation techniques, experimentation design, and failure analysis.
• Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity.
• Strong communication and collaboration skills in a distributed environment.

Bonus Points:

• Experience building ML or LLM platforms, tooling, or developer-facing frameworks.
• Prior work with embeddings, search–ranking systems, or advanced RAG architectures.
• Familiarity with event-driven systems or streaming architectures.
• Experience with model observability, performance monitoring, or proactive regression detection.
• Background in personalization, recommendations, or applied NLP.
• Experience working in remote-first engineering teams.

What we offer

• Competitive salaries & meaningful equity
• Private Medical Insurance
• Life/Risk Assurance
• Meal Allowance: 8.55€ per day
• Community Days (days for us to give back to the community)
• Paid Annual Leave (22 days)
• Global Lifestyle Reimbursement Account
• Paid Sabbatical
• Complete laptop workstation

The base salary range for this position in Lisbon, Portugal, is €66,500 – €88,000 per year (gross). This range is provided in anticipation of the requirements of the EU Pay Transparency Directive (2023/970), which EU member states are implementing into national law, and reflects the expected compensation at the start of employment for this role.The final offer will be determined based on your experience, qualifications, and performance throughout the selection process, while also ensuring alignment with our internal equity principles.