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Senior ML engineer

Summary

Build and deploy ML models for industrial digital twins, optimizing equipment performance and enabling data-driven decisions using Python, PyTorch/TensorFlow, and containerized pipelines.

This is us

At Avenga, we believe that human creativity empowers technology that matters. Operating globally, our 6000+ specialists provide a full spectrum of services, including business and tech advisory, enterprise solutions, CX, UX and Ul design, managed services, product development, and software development.

This is the job
We are looking for a Senior ML Engineer to join a team focused on building digital twin models of industrial equipment and systems. You will use experimental and observational data to iterate toward accurate models of complex industrial system behavior.

The goal is to create models that help optimize operations, predict equipment performance, and enable data-driven decision-making in industrial environments.

You will work across the full ML lifecycle: from data preprocessing and harmonization, through model selection and adaptation, to deployment and monitoring. You will own the infrastructure needed to support these models — whether by building it yourself or supervising LLM-assisted development to accelerate delivery.

This is you

  • Strong experience with Python and modern ML frameworks (PyTorch, TensorFlow, or similar)

  • Hands-on experience with deep learning model architectures — selecting, adapting, and fusing models to meet project goals

  • Experience preprocessing and harmonizing datasets from multiple sources

  • Solid understanding of experimental design and observational data analysis

  • Ability to document experiments and use insights to define production-ready solutions

  • Experience with Docker and containerized deployments

  • Upper-Intermediate or higher level of English

Nice-to-have skills:

  • Experience with A/B testing, recommender systems, or related adjacencies

  • Industrial software or industrial engineering experience

  • Familiarity with digital twin concepts or simulation-based modeling

  • Experience with MLOps practices (MLflow, experiment tracking, model versioning)

  • Knowledge of time-series forecasting, anomaly detection, or sensor data processing

  • Experience with cloud platforms (AWS, GCP, or Azure)

This is your role

  • Preprocess, clean, and harmonize datasets from various industrial sources to create model-ready inputs

  • Select, adapt, and potentially fuse existing deep learning model architectures to meet project requirements

  • Build the infrastructure (glue code, data pipelines, serving layers) to support models in production - manually or by supervising LLM-assisted development

  • Design and execute experiments to iterate toward accurate models of industrial system behavior

  • Document experiments, results, and lessons learned to inform production solution design

  • Collaborate with data engineers, domain experts, and other ML engineers to deliver scalable solutions

  • Ensure model reliability, performance, and observability in production environments

  • Contribute to architectural decisions, code reviews, and engineering best practices

What awaits you at Avenga?

At Avenga, everyone matters. We provide equal opportunities in recruitment, career development, and leadership, regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to fostering a work environment where our diverse community of employees, candidates, and business partners actively shapes our growth. By bringing together people from different backgrounds and experiences, we build a workplace where everyone feels free to be themselves while honoring the boundaries of others.

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