Job ID
- 67563
- Category
- Enterprise Technology
- Location
- Mexico City, Mexico, Remote
- Work Type
- Remote
- Develop prompt strategies, structured-output workflows, model routing, context-management approaches, and fine-tuning or adaptation methods when appropriate.
- Create rigorous LLM evaluation frameworks covering task quality, factuality, relevance, robustness, latency, cost, safety, and user experience.
- Explore and implement agentic AI patterns such as planning, tool and function calling, memory, reflection, human-in-the-loop approvals, and multi-step workflow execution.
- Develop and deploy scalable AI and machine learning solutions on GCP using services such as Vertex AI, BigQuery, Cloud Storage, Cloud Run, Cloud Functions, Pub/Sub, and related data and AI services.
- Create and maintain data pipelines that prepare structured and unstructured data for modeling, experimentation, evaluation, and production use.
- Perform exploratory analysis, feature engineering, statistical modeling, and machine learning to support broader data science needs.
- Communicate technical findings, tradeoffs, risks, and recommendations clearly to both technical and non-technical stakeholders.
- Stay current with emerging generative AI methods and translate promising research into practical business value.
**Education**:
Minimum:
- Bachelor’s degree in data science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience.
- Master’s degree or Ph.D. in a relevant quantitative or technical discipline
Preferred
**Experience**:
Minimum:
- 2+ years professional experience in data science, machine learning, applied AI, natural language processing, or a related technical role.
- 5+ years experience designing or deploying agentic AI systems,



including tool-using agents, graph-based workflows, multi-agent collaboration, or human-in-the-loop controls.
Preferred:
**Licenses and Certifications**:
- Licenses
**Work Requirements**:
Minimum
- Strong programming skills in Python and proficiency with SQL; experience writing maintainable, testable, production-quality code.
- Experience with prompt engineering, LLM evaluation, model integration, and core NLP concepts.
- Experience working with GCP data and AI services, particularly Vertex AI and BigQuery, or comparable experience on another major cloud platform with the ability to transition to GCP.
- Experience with modern software development and cloud deployment practices, including Git, APIs, containers, CI/CD, identity and access management, and production monitoring.
- Ability to translate ambiguous business needs into measurable technical objectives and deliver iteratively in a cross-functional environment.
- Strong analytical, problem-solving, documentation, and communication skills.
Preferred
- Hands-on experience with Vertex AI capabilities, including Model Garden, Generative AI Studio, custom training, model endpoints, pipelines, evaluation, and model monitoring.
- Experience building analytics and machine learning workflows with BigQuery, BigQuery ML, Dataflow, or related GCP services.
- Experience with fine-tuning, parameter-efficient adaptation, synthetic-data generation, distillation, or model serving and optimization.
- Experience developing evaluation datasets, automated evaluators, adversarial tests, red-team scenarios, and regression test suites for generative AI.
- Knowledge of LLMOps and MLOps practices, model and prompt versioning, experiment tracking, monitoring, scalable inference, and cost optimization.
- Experience delivering AI solutions in a regulated, safety-conscious, or large-enterprise environment.

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