Senior Machine Learning Engineer developing advanced ML and NLP solutions for Forrester’s conversational AI chatbot. Collaborating with cross - functional teams to deliver scalable, production - ready ML systems.
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
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Machine Learning Engineer designing GPU computing kernels to optimize 3D GenAI models at Meshy. Collaborating with researchers to enhance performance and efficiency in GPU module development.
Senior Software Engineer developing scalable machine learning solutions for product - driven team at Maropost. Collaborating on recommendation systems and enhancing developer experience within the Machine Learning team.
Principal MLOps Engineer leading design and optimization of machine learning infrastructure at Wood Mackenzie. Collaborating with data science and engineering teams to ensure robust automated ML lifecycles.
AI Engineer with expertise in Machine Learning for Periferia IT Group. Integrating generative AI models and developing solutions in a hybrid work environment.
Senior Platform/MLOps Engineer designing and maintaining scalable infrastructure for AI at Bright Machines. Join a team transforming manufacturing through intelligent automation.
CO
AI/ML Risk Guide enhancing risk management within Capital One's Tech and Product teams. Collaborating on risk solutions that impact customer experience and stability.
Staff Machine Learning Engineer developing content and creator classification systems for Patreon’s platform insights. Collaborating across teams to enhance discovery and recommendations for creators and fans.
Machine Learning Co - op working on sales and collection AI chatbot projects at Lendbuzz. Gaining experience with data annotation, cleaning, and multilingual model evaluation.
AI Prompt Senior Engineer developing and optimizing large language models for TIAA. Collaborating cross - functionally to create innovative AI solutions with a focus on data science.