Machine Learning Engineer

InteractiveAI; Madrid; Híbrido; EUR 60.000 - 120.000; Jornada completa

Descripción de la vacante

A rapidly growing AI startup in Madrid seeks a Machine Learning Engineer to design and productionize models, build scalable pipelines, and optimize ML systems. The ideal candidate has 3+ years in data engineering, strong Python skills, and experience in deploying models to production. Join a team focused on delivering impactful AI solutions, with competitive salary and hybrid work options.

Servicios

Competitive base salary

Performance bonuses

Private health insurance

Flexible work setup

25 days of paid time off

Formación

• 3 years in data engineering, ML engineering, or applied AI roles.
• Experience deploying models to production and optimizing inference performance.
• Fluent in Python for data and ML development.

Responsabilidades

• Design, train, and productionize models for our platform.
• Build and maintain scalable pipelines for data ingestion and transformation.
• Deploy ML models and ensure performance and reliability.

Conocimientos

Data engineering

Machine learning engineering

Python

Deep learning frameworks

Cloud platforms (AWS, GCP, Azure)

Communication skills

Educación

Experience in applied AI roles

Herramientas

Airflow

Spark

LangGraph

LlamaIndex

Descripción del empleo

What Youll Do

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

What Were Looking For

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)

What Youll Get

• 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)

Who You Are

• 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.

Interview Process

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

Were building a team of builders people who care about impact quality and growth. If thats you lets talk

About us

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.

Employment Type : Full-Time

Experience : years

Vacancy : 1