**_This is us

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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

At the intersection of Artificial Intelligence, industrial systems, and applied ML research, we are looking for a Senior Machine Learning Researcher to help design and validate novel ML approaches for understanding complex engineering systems from heterogeneous technical data.

The project is an early-stage R&D initiative focused on transforming industrial system descriptions, technical documentation, diagrams, specifications, and system data into structured representations that can support downstream modeling, simulation, and automation workflows.

The focus of the role has shifted toward a pure ML research profile rather than a primarily engineering / implementation profile. We are looking for someone who can explore research directions, design experiments, benchmark model approaches, and validate what is technically feasible in an ambiguous R&D environment.

This is the team

You’ll join a senior-level AI / ML research and engineering environment working on applied AI solutions for industrial system understanding. The team operates in an experimental R&D setup where scientific thinking, rapid hypothesis testing, and practical validation are equally important.

In this role, you’ll collaborate with AI engineers, domain experts, and technical stakeholders to explore ML approaches for extracting structure, relationships, and meaning from complex industrial data.

This is you

Strong background in machine learning research, applied ML, computer vision, multimodal learning, graph ML, representation learning, or related areas
Experience designing and running ML experiments, benchmarking models, and interpreting results
Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow
Ability to work with ambiguous research questions and translate them into testable hypotheses
Experience reading research papers and adapting methods to practical problems
Strong Python skills and ability to build research prototypes
Comfortable working independently in an R&D / PoC environment with evolving requirements
Strong commercial experience with Python and modern AI/ML ecosystems

Nice-to-have skills:

Experience with document understanding, diagram understanding, technical drawings, engineering schematics, or similar visual / structured data
Experience with knowledge graphs, graph neural networks, graph embeddings, or structured relationship modeling
Experience with vision transformers, VLMs, self-supervised learning, contrastive learning, or synthetic data generation
Experience with industrial, scientific, simulation, robotics, manufacturing, or physical-system data
Experience with multimodal data fusion, combining visual, textual, structured, or sensor-based data
Familiarity with GCP / Vertex AI or other cloud-based ML environments

This is your role:

Research and validate ML approaches for industrial system understanding
Explore methods for extracting entities, components, relationships, and structure from technical documents, diagrams, specifications, and other system descriptions
Design and run experiments comparing computer vision, multimodal, graph-based, and representation learning approaches
Build research prototypes and evaluation pipelines to test feasibility
Analyze model outputs, failure cases, and limitations, and propose improvements
Collaborate with AI engineers and domain experts to translate research findings into practical project direction
Present findings, experiments, and validation results to technical stakeholders

**_What awaits you at Avenga?

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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.