Data Engineer (LLM Applications)

FuseMachines; Ciudad de México; Híbrido; USD 40,000 - 60,000; Jornada completa

Descripción de la vacante

A leading AI provider seeks a skilled Data Engineer in Mexico City. This hybrid role involves developing LLM-based applications and working collaboratively with data scientists to implement innovative solutions. Candidates should have robust experience with Python, AWS, and a strong understanding of data engineering principles.

Formación

• 5+ years of experience in data engineering with strong expertise.
• Proven experience in developing and deploying machine learning APIs.
• Ability to work effectively in an agile team environment.

Responsabilidades

• Develop and implement applications that interact with LLM models.
• Build RAG-based applications and manage data for training.
• Collaborate with cross-functional teams to define and deploy new features.

Conocimientos

Python

APIs

AWS

Data Preprocessing

Problem Solving

Communication

Educación

Degree in Computer Science, Data Science, or a related field

Certifications in machine learning, data science, or cloud computing

Herramientas

Docker

Kubernetes

SQL

NoSQL databases

Spark

Hadoop

Descripción del empleo

About Fusemachines

Fusemachines is a leading provider of AI strategy, talent, and education services. Founded by Dr. Sameer Maskey, an Adjunct Associate Professor at Columbia University, our mission is to democratize AI. With a presence in four countries—Nepal, the United States, Canada, and the Dominican Republic—and a team of over 350 full-time employees, we leverage our global AI expertise to drive innovation and transformation for businesses worldwide.

This is a hybrid role that requires on-site presence for 2-3 days each week OR remote from other cities in Mexico.

About the role

We are looking for a skilled Data Engineer with a background supporting LLM applications to join our team. You will work closely with data scientists and be responsible for developing and implementing large language model (LLM)-based applications. This includes working with both proprietary and open-source models and leveraging frameworks such as LangChain to ensure seamless integration and deployment.

Responsibilities

• Develop and implement applications that interact with LLM models.
• Build RAG-based applications.
• Work with vector databases for LLM-based applications.
• Integrate models with existing systems and APIs.
• Develop and maintain production-quality data pipelines and ETL processes.
• Preprocess and manage data for training and deployment.
• Collaborate with cross-functional teams to define, design, and deploy new features.
• Write clean, maintainable, and efficient code.
• Document development processes, code, and APIs.

Requirements

• 5+ years of experience in data engineering, with strong expertise in Python, AWS and APIs.
• Proven experience in developing and deploying machine learning APIs.
• Experience in building scalable applications capable of handling large volumes of data.
• Strong knowledge of API integration (RESTful, GraphQL).
• Experience with data preprocessing, SQL, and NoSQL databases, as well as vector stores (e.g., Postgres, MySQL, Solr, Elasticsearch, OpenSearch).
• Familiarity with deployment tools (Docker, Kubernetes).
• Experience with DevOps tools such as Jenkins, Terraform, or Cloud Formation templates is a plus.
• Strong problem-solving and communication skills.
• Experience with distributed computing technologies such as Spark, Hadoop, or EMR is preferred.
• Ability to work effectively in an agile team environment.

Preferred Qualifications

• Degree in Computer Science, Data Science, or a related field.
• Certifications in machine learning, data science, or cloud computing.

Equal Opportunity Employer: Fusemachines is committed to fostering a diverse and inclusive workplace. We welcome applications from all qualified individuals regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, genetic information, disability, protected veteran status, or any other legally protected status.