About the Role
This position involves designing, building, and maintaining AI-driven systems that enhance core product capabilities. The engineer will collaborate with cross-functional teams to integrate machine learning models into production workflows and improve system intelligence.
Responsibilities
- Design and implement scalable machine learning systems
- Collaborate with product and data science teams to identify AI opportunities
- Develop and maintain production-grade AI models
- Optimize model performance and inference efficiency
- Integrate AI capabilities into existing software platforms
- Monitor and troubleshoot deployed models
- Ensure models meet reliability and accuracy standards
- Work with large-scale datasets for training and validation
- Apply natural language processing techniques where relevant
- Support the full lifecycle of AI development from prototyping to deployment
- Contribute to technical architecture decisions
- Write clean, maintainable, and well-documented code
- Participate in code reviews and technical discussions
- Stay current with advancements in AI and machine learning
- Improve data pipelines supporting AI systems
- Address ethical considerations in AI implementation
- Ensure compliance with data privacy standards
- Collaborate on model evaluation frameworks
- Drive automation of repetitive tasks using AI
- Support on-call rotations for critical systems
Nice to Have
- Master’s degree or higher in a technical discipline
- Direct experience with large language models
- History of contributing to open-source AI projects
- Experience in a remote-first company
- Familiarity with MLOps tools and practices
- Background in customer-facing AI applications
- Knowledge of responsible AI principles
Compensation
Competitive salary and benefits package
Work Arrangement
Remote position for candidates in Latin America
Team
Part of the engineering team focused on artificial intelligence and machine learning integration
About the Team
The engineering team works on integrating advanced AI capabilities into core product features. The group values technical excellence, collaboration, and continuous learning. Projects focus on real-world applications of machine learning to improve user productivity and system intelligence.
What Success Looks Like
Within the first six months, the engineer will have shipped multiple AI features to production, improved model reliability, and established strong collaboration with data science and product teams. Success is measured by system performance, team impact, and delivery consistency.
Not applicable; role is remote within Latin America
