AI Engineer
Globalli · Mexico · 2026-07-09
Sobre el puesto
We’re looking for a highly skilled AI Engineer to help us design, build, and scale intelligent systems across our next-generation global HR Tech platform. As an early-stage startup, we’re looking for someone who thrives in dynamic environments, is passionate about automation and AI-driven innovation, and brings hands-on experience developing AI/ML solutions within enterprise-grade SaaS platforms.
You’ll work cross-functionally with product, data, and engineering teams to develop models that improve user experience, automate decision-making, and support smart HR and payroll solutions. This role reports directly to the Head of Engineering.
What You’ll Do
• Design and implement machine learning models to solve HR-specific challenges (e.g., intelligent automation, anomaly detection, personalized experiences)
• Collaborate with product managers and engineers to bring AI features to life across the platform
• Develop and optimize data pipelines to support model training and inference
• Research and apply NLP, LLMs, and other AI/ML technologies to streamline and improve HR workflows
• Monitor model performance and retrain/improve based on feedback and usage
• Build scalable AI solutions using cloud-native tools (preferably AWS)
• Contribute to data governance, ethical AI use, and compliance
What You’ll Bring
• 4–6+ years of experience as an AI/ML Engineer or Data Scientist, ideally with startup or SaaS exposure
• Strong understanding of supervised/unsupervised learning, NLP, neural networks, and generative AI
• Proficiency with Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, or similar
• Experience deploying models in production using cloud platforms like AWS Sagemaker, GCP Vertex AI, or Azure ML
• Experience with data versioning, MLOps, and model lifecycle management
• Ability to work autonomously and thrive in a startup environment
• Familiarity with HR tech, payroll, or workforce data is a plus
Competencias solicitadas
- machine learning
- nlp
- aws
- python
- tensorflow
- pytorch
- gcp
- azure
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