AI Engineering Manager
Guadalajara, Jal., Mexico
MXN 600K-800K (estimate) Mid-level Full Time
Tasks
- Automate MLOps and LLMOps lifecycle
- Build and mentor AI engineering team
- Build inference infrastructure and CI CD pipelines
- Conduct technical reviews and architecture assessments
- Define AI system scope and limitations
- Deploy and monitor AI models
- Design APIs microservices and orchestration layers
- Design and deliver RAG systems
- Design evaluation frameworks for LLM systems
- Identify and categorize model failures
- Lead AI project delivery end to end
- Lead prompt engineering techniques
- Lead retraining workflows
- Perform feasibility assessments for AI approaches
- Run structured experiments and create metrics
Perks/Benefits
- Company-provided equipment
- English lessons
- Flexible working options
- Learning opportunities
- Mentorship programs
- Paid leaves
- Remote work bonus
- Study plans and courses
- Travel opportunities
- Udemy Business
Skills/Tech-stack
APIs | AWS | Automation | Azure | CI/CD | Databricks | Docker | Embeddings | Evaluation | Event Driven | Event-driven architecture | Few-Shot Learning | Few-shot | Fine Tuning | GCP | Git | Inference Optimization | Infrastructure as Code | Kubernetes | LLMOps | Language Models | Large Language Models | MLOps | MLflow | Microservices | Model Monitoring | Model versioning | Orchestration | Precision at K | Prompt engineering | Python | RAG | Recall at K | Reranking | Retrieval | Snowflake | Structured outputs | Weights and Biases | “as-code”
Education
N/A
Roles
AI | AI Engineering | AI Engineering Manager | Engineering | Engineering Manager | Manager
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