Machine Learning Engineer designing and optimizing deep learning models for safety - critical environments at Destinus. Shaping the future of high - speed, autonomous flight technologies.
About the role
- Senior Machine Learning Engineer leading cloud-hosted geospatial processing initiatives at Fugro. Translating business needs into technical plans and mentoring junior engineers in an agile environment.
Responsibilities
- Lead by example and place Quality, Health & Safety, Security, and the protection of the Environment as core values.
- Provide conceptual input and technical leadership in architecture and design discussions across ML, cloud, and geospatial workflows.
- Translate business needs into technical plans by understanding how Fugro’s products create value for clients and contributing actively to business value discussions.
- Drive end-to-end solution development: evaluate problem definition, requirements, feasibility, approach options, and proposed solutions.
- Design, build, and improve ML/Computer Vision solutions for feature extraction and classification from imagery and LiDAR.
- Assure efficiency and operational readiness of selected product components (reliability, scalability, performance, maintainability).
- Assure successful deployment of product/service/technology, including troubleshooting and resolution of operational issues.
- Document and demonstrate solutions with clear technical documentation and diagrams (flowcharts, layouts, architecture, data flows).
- Collect, analyze, and summarize development and service issues to improve platform quality and team execution.
- Actively drive knowledge exchange by leading design reviews, “known problems/solutions” sessions, and adoption of industry best practices.
- Support and develop less experienced engineers through coaching, mentorship, and opportunities for learning.
Requirements
- Legally authorized to work in the United States, without restrictions.
- Possess a Bachelor’s degree or Master’s degree preferred in Machine Learning, Data Science, Software Engineering, or a related engineering field.
- Have 5 years or more of professional experience building and maintaining software systems using relevant technologies preferred.
- Have 3 years or more of hands-on experience delivering machine learning solutions (including deep learning) to production or production-like environments preferred.
- Experience with Python required, C# desirable, or at least one additional language used in product development.
- Strong foundations in software engineering and system design (object-oriented design, testing, maintainability, reliability).
- MLOps experience (model packaging, deployment, monitoring, drift/quality checks, reproducible training).
- AWS (Amazon Web Services) cloud application development experience preferred.
- Strong written and verbal English communication skills; comfortable explaining technical tradeoffs to both technical and non-technical stakeholders.
- Geospatial data experience (raster/vector, coordinate systems, tiling) and/or remote sensing workflows is a plus.
- Experience with microservices architecture and container orchestration is also a plus.
- Experience with serverless and/or edge computing patterns is also a plus.
Benefits
- Opportunities to sharpen skills and provide career growth through on-the-job learning experiences
- LinkedIn Learning access
- Business and technical training
- Leadership development programs
- Flexible work models
Job title
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