Machine Learning Engineer - €60.000 - €120.000 A Year

What Youll DoAs a Machine Learning Engineer at InteractiveAI youll design train and productionize models that power our agentic platform.Embedded in a cross-functional squad youll build resilient data and model pipelines evaluate model quality with rigorous offline / online methods and ship performant inference services at scale.Youll collaborate closely with product and delivery to turn business problems into measurable ML solutions.Build and maintain scalable pipelines for structured / unstructured data ingestion transformation and feature engineeringTrain evaluate and iterate on ML models (including LLM fine-tuning where relevant) with strong experiment tracking and reproducibilityDeploy ML models and LLMs into production ensuring performance reliability observability and traceabilityImplement automated evaluation (A / B tests LLM-as-judge validation suites) and dashboards to monitor latency accuracy drift and trigger retraining or alertsApply feature engineering imputation and transformation techniques in practical production scenariosContribute to retrieval-augmented generation (RAG) workflows and measure retrieval and generation qualityIntegrate enterprise-grade agentic workflows and perform systematic evaluation of LLM outputsOptimize inference speed and memory usage in high-throughput systems; profile and reduce costwithout sacrificing qualityMonitor and improve model performance in production (latency accuracy drift data quality) with feedback loopsWork alongside product and delivery leads to ensure client-ready measurable outcomesWhat Were Looking ForWere looking for someone with strong foundations proven delivery and the ability to build production-ready ML systems.Heres what success looks like for this role :1 / Minimum Requirements :3 years in data engineering ML engineering or applied AI rolesExperience deploying models to production and optimizing inference performanceHands?on experience with at least one agent orchestration tool (e.G. LangGraph LlamaIndex)Experience training deep?learning models and fine?tuning LLMsFluent in Python for data and ML development and hands?on experience with at least one deep learning framework (PyTorch TensorFlow etc.)Experience building data pipelines (batch or streaming) using tools like Airflow SparkSolid grasp of ML concepts (bias?variance tradeoff supervised vs. unsupervised learning precision?recall tradeoffs)Comfortable working with cloud platforms (AWS GCP or Azure)Strong communication skills and experience working in cross?functional teams2 / Additional Requirements :Experience with LLMs and RAG pipelines in productionFamiliarity with vector databases embeddings and document retrieval strategiesExposure to MLOps practices : monitoring reproducibility CI / CD for MLExperience optimizing inference latency and cost at scaleExperience working in regulated or enterprise environments (e.G. banking insurance)What Youll GetCompetitive base salary (from *** / yr to **** / yr) performance bonusesFuture equity opportunity for high performersPrivate health insuranceFlexible work setup travel when needed (ideally Hybrid in Lisbon or Madrid)25 days of holidays / paid time off (excluding local public holidays)Who You AreProactive & Resourceful : You take initiative to identify gaps and drive solutions without waiting for instructions.Accountable & High-Ownership : You treat our codebase and infrastructure as your own and you honor commitments.Entrepreneurial Mindset : You thrive in ambiguity embrace rapid change and deliver in a high-paced startup setting.Team Player : You collaborate effectively across disciplines give and receive feedback constructively and mentor others.Interview ProcessWe keep our process focused and respectful of your time.Most candidates complete it in 23 weeks.Heres what to expect :Intro Call 30 minutes with our team to align on fit and expectationsTake-Home Challenge A practical task based on real-world problemsTechnical Interview Deep dive into the challenge technical experience and AI engineeringCultural and Values Interview Discussion on motivation cultural and value alignmentOffer Final conversation and offerWere building a team of builders people who care about impact quality and growth.If thats you lets talkAbout usInteractiveAI is a fast-growing startup on a mission to empower enterprises with fully managed AI agent lifecycles.We are building the next generation of enterprise-AI solutions delivering an end-to-end Agentic IDE alongside an extensible ecosystem of agentic resources and solutions.Our platform allows companies to orchestrate monitor evaluate deploy and improve AI agentsand soon fine?tune and own their own models.We value autonomy speed and innovation and were building a world?class team to match.Our squads are lean focused and execution?driven.If you thrive in high-performance environments and want to be part of a company that rewards transformational outcomes this is for you.Employment Type :Full-TimeExperience :yearsVacancy :1#J-*****-Ljbffr

and reduce costwithout sacrificing qualityMonitor and improve model performance in production (latency accuracy drift data quality) with feedback loopsWork alongside product and delivery leads to ensure client-ready measurable outcomesWhat Were Looking ForWere looking for someone with strong foundations proven delivery and the ability to build production-ready ML systems. Heres what success looks like for this role :1 / Minimum Requirements :3 years in data engineering ML engineering or applied AI rolesExperience deploying models to production and optimizing inference performanceHands?on experience with at least one agent orchestration tool (e.G. LangGraph LlamaIndex)Experience training deep?learning models and fine?tuning LLMsFluent in Python for data and ML development and hands?on experience with at least one deep learning framework (PyTorch TensorFlow etc.)Experience building data pipelines (batch or streaming) using tools like Airflow SparkSolid grasp of ML concepts (bias?variance tradeoff supervised vs. unsupervised learning precision?recall tradeoffs)Comfortable working with cloud platforms (AWS GCP or Azure)Strong communication skills and experience working in cross?functional teams2 / Additional Requirements :Experience with LLMs and RAG pipelines in productionFamiliarity with vector databases embeddings and document retrieval strategiesExposure to MLOps practices : monitoring reproducibility CI / CD for MLExperience optimizing inference latency and cost at scaleExperience working in regulated or enterprise environments (e.G. banking insurance)What Youll GetCompetitive base salary (from *** / yr to **** / yr) performance bonusesFuture equity opportunity for high performersPrivate health insuranceFlexible work setup travel when needed (ideally Hybrid in Lisbon or Madrid)25 days of holidays / paid time off (excluding local public holidays)Who You AreProactive & Resourceful : You take initiative to identify gaps and drive solutions without waiting for instructions.Accountable & High-Ownership : You treat our codebase and infrastructure as your own and you honor commitments.Entrepreneurial Mindset : You thrive in ambiguity embrace rapid change and deliver in a high-paced startup setting.Team Player : You collaborate effectively across disciplines give and receive feedback constructively and mentor others.Interview ProcessWe keep our process focused and respectful of your time.

Heres what to expect :Intro Call 30 minutes with our team to align on fit and expectationsTake-Home Challenge A practical task based on real-world problemsTechnical Interview Deep dive into the challenge technical experience and AI engineeringCultural and Values Interview Discussion on motivation cultural and value alignmentOffer Final conversation and offerWere building a team of builders people who care about impact quality and growth. If thats you lets talkAbout usInteractiveAI is a fast-growing startup on a mission to empower enterprises with fully managed AI agent lifecycles.We are building the next generation of enterprise-AI solutions delivering an end-to-end Agentic IDE alongside an extensible ecosystem of agentic resources and solutions.Our platform allows companies to orchestrate monitor evaluate deploy and improve AI agentsand soon fine?tune and own their own models.We value autonomy speed and innovation and were building a world?class team to match. Our squads are lean focused and execution?driven.If you thrive in high-performance environments and want to be part of a company that rewards transformational outcomes this is for you.Employment Type :Full-TimeExperience :yearsVacancy :1#J-*****-Ljbffr