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Selected role

Senior ML Computer Vision Engineer

N-iX En remoto, ES

Senior Full-time

We are looking for a Senior ML Computer Vision Engineer to join our team!

Our client is an innovative technology division within one of the world's top-10 copper producers. You'll play a pivotal role in their expanding Computer Vision and AI ambitions. While the initial focus involves advanced asset management, the team is embarking on a long-term journey to leverage traditional machine learning, artificial intelligence, and predictive maintenance across their global operations.

Working closely with a newly appointed Computer Vision Subject Matter Expert (SME) and cross-functional data and integration teams, you will drive research and development initiatives from proof-of-concept through to production. Your work will directly shape how the organisation utilizes visual and operational data, eventually integrating these cutting-edge AI capabilities into the core asset management scope and broader operational ecosystem.

Responsibilities:

Partner with the Computer Vision SME to drive R&D initiatives, exploring new applications for AI, CV, and traditional machine learning within heavy industry.
Design, develop, and deploy Computer Vision models (e.g., object detection, image classification, segmentation) and traditional ML algorithms for predictive maintenance and asset monitoring.
Translate business requirements and R&D concepts into scalable, production-ready machine learning pipelines.
Collaborate with Data Engineers and Analytics Engineers to ensure seamless ingestion, transformation, and availability of visual, sensor, and operational data.
Work alongside Integration Engineers to embed AI/ML capabilities and model outputs into existing enterprise applications and asset management systems.
Implement MLOps best practices for model training, versioning, deployment, monitoring, and lifecycle management within an Azure-centric environment.
Evaluate and select appropriate algorithms, frameworks, and cloud-native AI tools to meet evolving business and performance needs.
Prepare comprehensive technical documentation, model architectures, and performance reports for technical and non-technical stakeholders.

Requirements:

5+ years of hands-on experience as a Machine Learning Engineer, Computer Vision Engineer, or AI Researcher in a software development environment.
Strong proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or Keras.
Proven experience building and deploying Computer Vision solutions (e.g., using OpenCV, YOLO, ResNet) in real-world scenarios.
Solid foundation in traditional machine learning techniques (e.g., scikit-learn, XGBoost) and statistical data analysis, particularly for predictive maintenance or time-series forecasting.
Experience with cloud-based ML platforms and MLOps practices, preferably utilizing Azure Machine Learning, Databricks, or similar enterprise environments.
Familiarity with data manipulation and analysis libraries (Pandas, NumPy) and working with large, diverse datasets (images, video streams, sensor data).
Strong analytical and problem-solving skills, with a track record of transitioning models from R&D phases into production scale.
Excellent communication skills, with the ability to collaborate effectively with SMEs, data engineering teams, and business leadership.
Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, or a related highly quantitative field (or equivalent applied experience).

Nice to have:

Background in mining, heavy industry, or manufacturing environments, particularly working with OT (Operational Technology) or IoT sensor data.
Experience processing and analyzing geospatial data, drone imagery, or edge-computing AI deployments.
Familiarity with Azure Data Factory, Azure Synapse, or Azure Integration Services to better align with the broader data platform team.

We offer*:

Flexible working format - remote, office-based or flexible
A competitive salary and good compensation package
Personalized career growth
Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
Active tech communities with regular knowledge sharing
Education reimbursement
Memorable anniversary presents
Corporate events and team buildings
Other location-specific benefits
not applicable for freelancers

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