AI/ML Engineer

AI / ML Engineer at DataDope

Join DataDope as an AI / ML Engineer and build intelligent solutions that combine data, models, and autonomous agents applied to complex observability and network systems. If you enjoy designing AI systems integrating Machine Learning, LLMs, and real-time operational data, developing intelligent agents to analyze events, alerts, and metrics, and deploying them robustly and scalably, we want you on our team!

What you will do at DataDope:

• Transform business challenges into end-to-end AI / ML solutions, deeply understanding business objectives.
• Design, develop, and deploy Machine Learning models and AI agent workflows for anomaly analysis, prediction, classification, and correlation of events, networks, and user experience.
• Implement autonomous agents and decision systems using frameworks like LangGraph, CrewAI, OpenAI, and AutoGen.
• Develop LLM-based agents capable of analyzing operational events, alerts, metrics, and logs.
• Design automated reasoning systems to help explain incidents or recommend actions on observability platforms.
• Integrate LLMs with internal data (RAG) using vector databases like Chroma or Pinecone.
• Collaborate with Data Engineers to design reproducible and scalable training and inference pipelines (Spark, Airflow, MLflow).
• Develop backend components, MCPs, and APIs (Python / FastAPI) to expose models or agents to products.
• Create and maintain reproducible experimentation environments (Docker, conda/pipenv, Jupyter).
• Document experiments, metrics, hyperparameters, and validation results with traceability and quality.
• Collaborate closely with Data Science, Data Engineering, and DevOps/MLOps teams to integrate models into production pipelines.
• (Advanced Plus) Design hybrid architectures combining traditional ML, generative AI, and structured knowledge (Graph / RAG).
• Collaborate with the team and guide junior profiles, sharing knowledge and best practices.

What we need from you:

• Education in Computer Science, Mathematics, Engineering, or quantitative disciplines.
• Experience in developing and implementing Machine Learning or AI models.
• Solid Python experience, with expert handling of Pandas and NumPy.
• Proficiency in scikit-learn, StatsModels, and Deep Learning frameworks (TensorFlow, PyTorch).
• Real-world experience in time series forecasting, beyond basic statistical models (plus).
• Autonomy and team spirit, as we like to learn together at DataDope.
• Experience in training, tuning, and deploying ML models (supervised and unsupervised).
• Hands-on experience with agent and LLM orchestration frameworks (LangGraph, CrewAI, AutoGen).
• Experience with vector databases and RAG techniques (Retrieval-Augmented Generation).
• Experience with data pipelines and training.
• Ability to analyze model results and metrics.
• Skill in documenting and communicating technical results clearly and structuredly.

If you also have:

• Knowledge of cloud platforms (AWS, GCP, Azure).
• Experience with NoSQL databases (MongoDB, ClickHouse) and technologies like Kafka.
• Experience with generative AI and open-source LLMs (OpenAI, Anthropic, Mistral, Ollama, Hugging Face).
• Knowledge of Graph Databases and Knowledge Graphs.
• Familiarity with multi-role or multi-modal agent topologies.
• Knowledge in model optimization (quantization, distillation, LoRA fine-tuning).
• Experience in monitoring and continuous evaluation of models in production (Prometheus, EvidentlyAI, Arize).
• Knowledge in MLOps: MLflow, DVC, Docker, CI/CD, model versioning, and experiment tracking.

We offer:

• A collaborative, inclusive, and innovation-oriented work environment.
• Exciting projects that will challenge your skills and allow you to grow professionally.
• Leadership and personal growth opportunities.
• Competitive salary commensurate with your experience and the role's responsibilities.
• Flexible working hours with a remote model (with the possibility of hybrid if you reside in Madrid).
• Reduced working hours on Fridays, July, and August.
• 25 days of vacation + your birthday off.
• Flexible benefits package.

Interested?

If you feel this role is for you and you want to be part of the team redefining the future of observability, we would love to hear from you! You can send your CV directly to rrhh@datadope.io

Join DataDope and lead the observability revolution!

Key skills/competency:

• AI/ML Engineer
• Machine Learning
• LLMs
• Autonomous Agents
• Observability
• Python
• Deep Learning
• Data Pipelines
• MLOps
• Cloud Platforms