AI/ML ENGINEER

At Ayesa Digital, we grow with you.

Every professional in our company is essential. Thanks to their talent, we continue to expand: today, we are a global team of more than 11,000 people working toward a shared mission.

Ayesa Digital is currently participating in high-impact European Union projects designed to address major European challenges and drive science and innovation. These strategic technological initiatives stand out for their international scope and strong commitment to socially oriented results.

We are looking for a AI/ML Engineer to join our international team and contribute to the developing, training and maintenance of the machine learning models and software applications in the fields of Nature Language Processing (NLP) and Artificial Intelligencia (AI), including the application of Large Language Models (LLMs) and generative AI for specific use cases.

Key Responsibilities

• Deploy generative AI models or integrate their APIs, and Retrieval Augmented Generation (RAG) techniques.
• Select features, build and optimize classifiers using machine learning techniques.
• Perform studies and developments aiming at improving the quality of machine translation (MT) engines for each installed language pair, addressing the specific needs of customers of the service concerning MT quality and contributing to a general strategy for the systematic evaluation and long-term improvement of MT quality.
• Interact with data stewards and other IT stakeholders to define the data rules.
• Define data controls and implement strategies to ensure data quality, integrity, and the detection and mitigation of bias in datasets and AI models.
• Create automated anomaly detection systems and constant tracking of its performance.
• Perform processing, cleansing, and verifying the integrity of data used for analysis.
• Design and propose the technical architecture for NLP/ML/AI solutions, coordinating its implementation with engineering teams while adhering to data management principles (master data management, metadata).
• Assess data architecture against quality dimensions (consistency, completeness, accuracy, reasonableness) and recommend target-state improvements.
• Draft technical guidelines, documentation, and presentations to effectively communicate complex AI concepts, project status, and results to both technical and non-technical stakeholders.
• Ensure compliance with data protection and AI Act regulations.
• Implement MLOps practices to automate the machine learning lifecycle, including continuous integration, delivery, and monitoring (CI/CD/CD) of models.
• Monitor model performance in production, identifying model drift and initiating retraining processes to maintain accuracy and relevance.
• Stay abreast of the latest academic and industry research in AI/ML to propose and pilot innovative solutions that provide competitive advantage.

What We Are Looking For (Requirements):

• Excellent knowledge of programming languages essential for AI/ML, primarily Python and R, and their key libraries (e.g., TensorFlow, PyTorch, scikit-learn, pandas, SpaCy, NLTK).
• Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks.
• Good knowledge of cloud tools for Fine tuning or training Models, like AWS SageMaker or Azure Machine Learning Studio.
• Good knowledge of cloud platforms for building LLM solutions (e.g., AWS Bedrock, Azure AI Studio) and frameworks for orchestration (e.g., LangChain, LlamaIndex) and safety/guardrails.
• Good knowledge of AI Agent Orchestration frameworks, like Langchain or Semantic Kernel.
• Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures, testing methodologies and tools, such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality.
• Knowledge of query languages, such as SQL, Hive, Pig, etc and with information extraction
• Knowledge of data visualisation tools, such as D3.js, GGplot, etc
• Knowledge of NoSQL databases, such as MongoDB, Cassandra, HBase, etc
• Knowledge of relevant elements of cybersecurity of AI systems
• Knowledge of the relevant aspects of the AI Act and AI risks.
• Experience with MLOps practices and tools for model versioning, deployment, monitoring, and governance (e.g., MLflow, Kubeflow).
• Knowledge of techniques for responsible AI, including bias detection and mitigation (e.g., IBM AIF360, Fairlearn) and model explainability (e.g., SHAP, LIME)
• Good level of English, optionally French as an additional asset.

One of the following or an equivalent certification:

• AWS Certified Machine Learning
• Specialty, Microsoft Azure AI Engineer Associate,
• SAS Certified Professional AI and Machine Learning.

What We Offer:

• Prestigious projects within European institutions.
• International, innovative, and multicultural environments.
• Continuous support from a team of experts in EU projects.

If you are ambitious, enthusiastic, and seeking a new professional challenge in international projects with real-world impact, this is the place for you!

In accordance with Organic Law 3/2007 of March 22, the company is committed to promoting the defense and effective application of the principle of equality between men and women, preventing any type of labor discrimination based on sex, and guaranteeing equal entry opportunities. Furthermore, we promote diversity and reject any discrimination based on race, gender, functional diversity, religion, sexual orientation, gender identity, or any other personal or social condition, striving to build an inclusive and enriching environment.