We are looking for a Lead Machine Learning Engineer to support a large-scale Asset Image Analytics initiative for a major utilities client, focused on leveraging computer vision and AI to improve asset inspection, risk detection, and operational decision-making.
This role will contribute to the end-to-end development of ML pipelines, including image ingestion, labeling, model development, and deployment, enabling capabilities such as automated defect detection, asset classification, and predictive insights.
You will work closely with data scientists, engineers, and client stakeholders to build scalable solutions that transform imagery data into actionable intelligence for asset management.
Key Responsibilities
- Design, develop, and deploy machine learning models, with a focus on computer vision (CV) use cases such as defect detection, classification, and change detection.
- Build and maintain ML pipelines, including preprocessing, feature engineering, model training, and validation workflows.
- Collaborate with cross-functional teams to support image labeling, dataset creation,



and model training processes.
- Develop and optimize image ingestion and metadata enrichment pipelines to support scalable analytics
- Integrate ML outputs into downstream systems (e.g., asset management platforms, workflow tools) to enable automated insights and actions.
- Improve model performance through continuous evaluation, tuning, and retraining strategies.
- Support deployment and operationalization of models (MLOps), including monitoring and performance tracking.
- Partner with stakeholders to translate business requirements into data science and ML solutions aligned to asset management use cases.
- Contribute to the development of AI/ML best practices, governance, and scalable architecture.

Qualifications
- 10-15+ years of experience as a machine learning (MLOps), data, and/or software engineer using Python in a production environment.
- Experience building, deploying, and optimiz

📌 Senior Machine Learning Engineer with Geospatial and Utilities Focus (Argentina)
🏢 Fundamentl
📍 Argentina