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Location
Hybrid (Mexico)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. Avenga scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Avenga is an IT engineering and consulting company formed in 2019 through the merger of several European software services firms. It provides custom software development, AI and data solutions, cloud engineering, managed IT operations and customer experience design for clients in life sciences, financial services, insurance, telecommunications and manufacturing. It is headquartered in Prague, Czech Republic, and runs delivery centers in Poland, Ukraine, North Macedonia, Bulgaria, Latin America and Asia, where it hires SRE, AI, PHP and IT operations engineers and solution architects.

Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets.

At the core of the role

We are actively seeking an experienced AI Solutions Architect / Senior AI & Machine Learning Engineer to join a technology-driven project focused on designing and implementing advanced Artificial Intelligence and Data Science solutions.

In this role, you will be responsible for defining scalable AI and Machine Learning architectures, developing and optimizing models, and deploying them into production environments. You will work across the full AI lifecycle, from data preparation, statistical modeling, and experimentation to production deployment, monitoring, and optimization.

You will collaborate with technical and business stakeholders to transform complex requirements into robust, scalable AI solutions, working with modern cloud and Big Data ecosystems. The role offers the opportunity to work with traditional Machine Learning techniques as well as emerging technologies such as Large Language Models (LLMs) and Prompt Engineering.

Core skills you’ll bring

  • Strong experience designing and implementingArtificial Intelligence, Machine Learning, and Data Science architectures.

  • Advanced knowledge of Machine Learning algorithms, including Decision Trees, Random Forest, SVM, K-Means, Naive Bayes, KNN, and Neural Networks.

  • Strong hands-on development experience with Python and Shell Scripting.

  • Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn.

  • Hands-on experience working with Large Language Models (LLMs) and Prompt Engineering.

  • Strong knowledge of advanced statistical techniques, including statistical modeling, clustering, and predictive analytics.

  • Experience developing and optimizing SQL queries.

  • Experience defining data quality, control, validation, and assurance mechanisms.

  • Experience deploying Machine Learning models into production environments using Docker and Kubernetes.

  • Experience with Big Data and cloud ecosystems, such as Cloudera, AWS, Azure, or GCP.

  • Knowledge of real-time and batch data processing.

  • Experience with advanced model optimization and hyperparameter tuning.

  • Availability to work under a hybrid model, attending the office three days per week.

  • Availability to travel when required by business or operational needs.

Nice-to-have

  • Experience designing end-to-end AI solutions across complex or large-scale environments.

  • Exposure to multiple cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP).

  • Experience integrating LLMs and Generative AI solutions into enterprise applications or business workflows.

  • Knowledge of MLOps practices and model lifecycle management.

  • Experience working with large-scale or distributed data environments such as Cloudera.

  • Strong communication skills and experience collaborating with multidisciplinary technical and business teams.

The impact you'll create

  • Design and implement scalable AI, Machine Learning, and Data Science architectures aligned with business and technical requirements.

  • Develop, train, validate, optimize, and deploy Machine Learning models into production environments.

  • Build AI solutions leveraging both traditional Machine Learning algorithms and Large Language Models.

  • Define reliable data quality, validation, and control mechanisms to support AI initiatives.

  • Optimize model performance through advanced statistical techniques and hyperparameter tuning.

  • Support real-time and batch data processing scenarios across cloud and Big Data environments.

  • Collaborate with engineering, data, and business stakeholders to translate complex challenges into production-ready AI solutions.

  • Contribute to the continuous improvement and evolution of the organization's Artificial Intelligence capabilities.

People are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to a respectful environment where everyone can be themselves, share their ideas, and feel that they belong.

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