Brazil
GFT Technologies SE
UL Solutions
Machine Learning Engineer
Brazil
São Paulo, São Paulo, Brazil
Python
About the opportunity
The AI Engineer is responsible for delivering value through the delivery of AI solutions to core business functions. This role focuses on applying industry AI techniques, tools, and platforms to develop scalable, production-ready systems that solve real business problems.
As a highly collaborative and delivery-focused contributor, you will own defined initiatives end-to-end, ensuring measurable impact while working closely with product, wider engineering teams, and business stakeholders. You will balance technical excellence with strong ways of working, contributing to a culture of accountability, trust, and continuous improvement.
This role requires strong applied AI engineering skills across architecture, software engineering, and MLOps, combined with the ability to communicate effectively and drive business-aligned outcomes.
Our science is your advantage.
Responsibilities
- Own and deliver AI-enabled features or initiatives (1–3 people scope) that provide measurable business value
- Deliver against defined acceptance criteria while balancing speed, quality, maintainability, and predictability
- Contribute to backlog refinement to translate business problems into applied AI solutions and ensure outcomes are tied to measurable impact
- Contribute to solution architecture aligned with scalability, security, and cost considerations
- Work with reference architectures, contributing reusable patterns and improvements
- Build and maintain CI/CD pipelines for AI services and supporting infrastructure
- Implement MLOps practices for training, deployment, monitoring, and lifecycle management
- Ensure solutions meet security, compliance, and operational requirements
- Design and build production-ready AI systems using modern software engineering practices
- Develop clean, maintainable, and well-tested Python code following best practices (TDD, modularity, reuse)
- Apply industry solutions such as:
- Retrieval-Augmented Generation (RAG)
- Document intelligence / document-to-data pipelines
- Agentic workflow systems
- Integrate AI capabilities into scalable applications and enterprise systems
- Apply structured experimentation and evaluation methods to AI systems
- Design and apply production evaluation mechanisms to support A/B testing and equivalent
- Use metrics to validate performance, quality, and business impact
- Continuously improve solutions through feedback, monitoring, and iteration
- Clearly communicate technical concepts, trade-offs, and outcomes to both technical and non-technical stakeholders
- Participate in demos, design discussions, and cross-functional collaboration
- Frame work in terms of business value and measurable outcomes
- Actively contribute to a culture of trust, psychological safety, and accountability
- Collaborate effectively within squad and across teams to achieve shared outcomes
- Support and mentor junior team members through knowledge sharing and guidance
- Provide and seek constructive feedback to improve team performance
- Perform other duties as directed.
Qualifications
- Bachelor’s degree in Data Analytics, Data Science, Computer Science, or related field (Master’s preferred).
- Experience delivering production software or AI solutions in a team environment
- Strong Python programming skills with focus on production-quality code
- Experience working with:
- AI/ML systems (LLMs, NLP, or similar)
- APIs and system integration
- Cloud platforms (preferably Azure)
- Experience with DevOps and CI/CD practices focused on IaC
- Experience with evaluating AI and probabilistic systems through measurement-based experiments
- Familiarity with MLOps pipelines and model lifecycle management
- Experience designing scalable architecture for AI solutions
- Understanding of responsible AI, security, networking, and compliance considerations
- Strong collaboration and teamwork mindset, contributing to shared team success over individual output
- Clear and effective communication across diverse teams and stakeholders
- Ability to own problems end-to-end and deliver outcomes with minimal supervision
- Proactive mindset with focus on continuous improvement and learning
- Ability to balance technical excellence with business priorities
- Demonstrated accountability and ownership of commitments
- Adaptability and openness to change in a fast-evolving AI environment
- Strong capability to coordinate and communicate with colleagues across diverse geographic regions, cultures, and time zones.
A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. UL Solutions delivers testing, inspection and certification services, together with software products and advisory offerings, that support our customers’ product innovation and business growth. The UL Mark serves as a recognized symbol of trust in our customers’ products and reflects an unwavering commitment to advancing our safety mission. We help our customers innovate, launch new products and services, navigate global markets and complex supply chains, and grow sustainably and responsibly into the future.
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