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.

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.

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