Machine Learning Engineer

As 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 engineering
• Train evaluate and iterate on ML models (including LLM fine-tuning where relevant) with strong experiment tracking and reproducibility
• Deploy ML models and LLMs into production ensuring performance reliability observability and traceability
• Implement automated evaluation (A / B tests LLM-as-judge validation suites) and dashboards to monitor latency accuracy drift and trigger retraining or alerts
• Apply feature engineering imputation and transformation techniques in practical production scenarios
• Contribute to retrieval-augmented generation (RAG) workflows and measure retrieval and generation quality
• Integrate enterprise-grade agentic workflows and perform systematic evaluation of LLM outputs
• Optimize inference speed and memory usage in high-throughput systems; profile and reduce cost without sacrificing quality
• Monitor and improve model performance in production (latency accuracy drift data quality) with feedback loops
• Work alongside product and delivery leads to ensure client-ready measurable outcomes

Were 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 roles
• Experience deploying models to production and optimizing inference performance
• Hands-on experience with at least one agent orchestration tool (e.g. LangGraph LlamaIndex)
• Experience training deep-learning models and fine-tuning LLMs
• Fluent 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 Spark
• Solid 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 teams

2 / Additional Requirements :

• Experience with LLMs and RAG pipelines in production
• Familiarity with vector databases embeddings and document retrieval strategies
• Exposure to MLOps practices : monitoring reproducibility CI / CD for ML
• Experience optimizing inference latency and cost at scale
• Experience working in regulated or enterprise environments (e.g. banking insurance), * Proactive & 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.

• Competitive base salary (from 60000 / yr to 120000 / yr) performance bonuses
• Future equity opportunity for high performers
• Private health insurance
• Flexible work setup travel when needed (ideally Hybrid in Lisbon or Madrid)
• 25 days of holidays / paid time off (excluding local public holidays), We 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 expectations
• Take-Home Challenge A practical task based on real-world problems
• Technical Interview Deep dive into the challenge technical experience and AI engineering
• Cultural and Values Interview Discussion on motivation cultural and value alignment
• Offer Final conversation and offer

InteractiveAI 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.