Senior ML Computer Vision Engineer

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.

Do you have a Master’s degree?, * 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.

• 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