Machine Learning Engineer - LLM

Role: Machine Learning Engineer - LLM Platforms & Assistants

Apply by Whats App: 55 61 4646 51

Requirements

Bachelor’s Degree in Computer Science, Engineering, Data Science, or equivalent experience.

Gross Salary: $75,000 MXN / Month

Summary Role

• The Machine Learning Engineer will support the transition from custom GPT prototypes to production-grade, action-driven AI assistants.
• This role focuses on designing and implementing modular LLM pipelines using Python, Retrieval-Augmented Generation (RAG) and Lang Chain, integrating enterprise data systems and emerging tools such as MCP and SnapLogic.
• The engineer will design, build, and operate production-grade Large Language Model (LLM) pipelines in AWS environments, integrating OpenAI models into modular Python services while enabling scalable, secure, and observable AI assistants.

Experience and Responsibilities & Qualifications

• With over 5 years of experience in software engineering, machine learning engineering, or applied AI roles.
• Strong Python programming skills.
• Experience implementing RAG pipelines and semantic search architectures.
• Hands-on experience integrating OpenAI LLM APIs into applications.
• Experience deploying systems within AWS environments (S3, Lambda, ECS/EKS, IAM).
• Preferred
• Experience with Amazon SageMaker or Amazon Bedrock.
• Familiarity with AWS data services such as Glue, Athena, OpenSearch, or Aurora.
• Experience building ETL/ELT data pipelines supporting ML workflows.
• Knowledge of LLM orchestration frameworks, reasoning workflows, and evaluation/benchmarking techniques.
• Experience integrating SnapLogic pipelines.
• Familiarity with Craxel Black Forest Timeseries DB (training provided).
• Experience with Infrastructure as Code tools such as CDK, CloudFormation, or Terraform.
• Design and maintain LLM integrations using OpenAI APIs within AWS environments.
• Build and deploy Python-based LLM services on AWS computer platforms such as ECS, EKS, Lambda, or EC2.
• Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search using AWS data and storage services.
• Develop Lang Chain-based or agentic workflows that support reasoning, tool usage, and modular orchestration.
• Integrate LLM pipelines with enterprise ETL/ELT workflows and data systems, including SnapLogic.
• Deploy and integrate MCP servers and orchestration frameworks for scalable AI assistant workflows.
• Apply AWS security best practices using IAM, KMS, and Secrets Manager to protect data and model interactions.
• Implement monitoring, logging, and observability using CloudWatch and related AWS tools.
• Support the migration of custom GPT prototypes into production-grade AWS-hosted assistants.

Soft Skills

• Strong Analytical
• Problem - Solving
• Ability to communicate clearly
• Strong Sense of Ownership
• Accountability
• Responsibility
• Adaptability