Full Stack Applied AI Engineer
Role details
Job location
Tech stack
Job description
- Develop and maintain applications and services integrating AI models.
- Collaborate with teams to deploy secure and scalable environments.
- Monitor and optimize AI applications performance.
Conocimientos
Python AI and ML engineering Azure and cloud technologies Software engineering principles CI/CD practices MLOps tools Docker and Kubernetes Observability tools Data processing libraries LLM frameworks, * Develop and maintain applications and services that make AI accessible to internal and external users, integrating AI models into existing applications, APIs, and systems.
- Collaborate with infrastructure and DevOps teams to deploy secure and scalable cloud and on-premise environments (including GPU partitioning), optimizing performance, resources, and costs.
- Partner with AI Engineers and cross-functional teams to transform prototypes into robust, production-grade AI solutions.
- Monitor and optimize the performance of AI applications, implementing observability best practices (logging, metrics, alerting) to detect incidents, data drift, and model deviations in production environments.
- Stay up to date with the latest developments in AI frameworks, cloud technologies, and software engineering practices, applying relevant improvements to production systems.
Requirements
A leading multinational organization in Málaga is seeking a Full Stack Applied AI Engineer to develop and maintain AI applications, optimize performance, and collaborate with cross-functional teams. Ideal candidates have a Bachelor's degree and 4+ years of experience in AI or ML engineering, with strong programming skills in Python and familiarity with cloud technologies. This role offers excellent career growth opportunities., * 4+ years of experience in AI, Data Science, or ML Engineering applied to real-world environments.
- Experience developing and deploying AI or ML solutions in Azure.
- Hands-on experience with CI/CD pipelines and DevOps practices., Bachelor's degree in Computer Science, Engineering, or STEM, * Bachelor's degree in Computer Science, Engineering, or another STEM field.
- 4+ years of experience in AI, Data Science, or ML Engineering applied to real-world environments.
- Strong programming skills in Python and solid understanding of software engineering principles (testing, clean code, CI/CD).
- Experience developing and deploying AI or ML solutions in Azure (e.g., Azure Machine Learning or Azure AI Services).
- Proficiency with PyTorch, FastAPI, and data/ML libraries such as Pandas or Scikit-learn.
- Experience with MLOps tools such as MLflow, Airflow, or Dagster.
- Experience with LLM frameworks (HuggingFace, LangChain, LlamaIndex) and agent-based automation (CrewAI, Agno, MCP, etc.).
- Knowledge of cloud-native infrastructure (Docker, Kubernetes, GPU partitioning).
- Familiarity with observability and model monitoring tools (EvidentlyAI, InspectAI, DeepEval).
- Experience with vector databases (Milvus, OpenSearch).
- Familiarity with distributed data processing (Dask, Polars) and LLM optimization (LoRA, QLoRA).
- Hands-on experience with CI/CD pipelines (GitHub Actions) and DevOps practices.