Data & Machine Learning Engineer in Mexico at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data & Machine Learning Engineer based in Mexico.

As a Data & Machine Learning Engineer, you will play a key role in building and evolving end-to-end data and AI systems that power advanced analytics, machine learning, and LLM-driven applications. In this role, you will design scalable data pipelines, develop ML-enabled workflows, and enable intelligent, data-driven products across the organization. You will work at the intersection of data engineering, MLOps, and AI innovation, contributing to architectures that support both structured and unstructured data at scale. This is a highly technical, hands-on role within a global data team where your work directly enables smarter business decisions and next-generation AI capabilities. You will also collaborate closely with BI and engineering stakeholders in a fast-paced, English-speaking environment.

• Design, build, and maintain scalable data pipelines supporting ingestion, transformation, and delivery into data warehouses, feature stores, and ML/AI systems.
• Develop workflows for processing unstructured data and building semantic representations to enable advanced search, retrieval, and LLM-powered applications.
• Build and optimize analytics and BI solutions, including natural language querying and AI-driven insight generation.
• Implement and manage LLM-related workflows, including prompt engineering, orchestration pipelines, and model fine-tuning processes.
• Design and maintain vector database solutions and indexing strategies to support retrieval-augmented generation (RAG) systems.
• Collaborate with stakeholders to translate business and product requirements into scalable data and ML solutions.
• Ensure proper documentation of data pipelines, ML workflows, and deployment processes to maintain transparency and reproducibility.
• Stay up to date with emerging trends in data engineering, MLOps, and LLM technologies, contributing to continuous improvement.

• Minimum of 8 years of experience in Data Engineering, with at least 2 years focused on MLOps or machine learning workflows.
• Strong proficiency in Python for large-scale data processing, transformation, and engineering tasks.
• Solid experience designing and maintaining distributed data pipelines using tools such as Apache Spark, Hadoop, and Kafka.
• Deep understanding of SQL and relational database systems, including BI and data warehousing methodologies (e.g., Snowflake, Redshift).
• Hands-on experience with vector databases and RAG architectures for semantic search and LLM applications.
• Experience integrating LLM frameworks into production systems, including inference, fine-tuning, and orchestration.
• Familiarity with cloud platforms such as AWS or Azure, particularly for ML and data workloads.
• Strong understanding of software engineering principles, version control, CI/CD, and Agile development practices.
• Excellent communication skills in English, with the ability to collaborate across technical and business teams.
• Strong analytical mindset with a clear understanding of how data systems support business intelligence and decision-making.

• Fully remote opportunity with flexibility to work across LATAM regions.
• Competitive compensation package aligned with experience.
• Opportunity to work on cutting-edge AI, LLM, and machine learning systems at scale.
• Exposure to global data infrastructure, advanced analytics, and enterprise-grade BI systems.
• Collaborative, international team environment with strong technical expertise.
• Career development opportunities in data engineering, MLOps, and AI innovation.
• Work on high-impact projects involving real-time data, semantic search, and intelligent automation.
• Opportunity to contribute to modern AI-driven data platforms used in large-scale enterprise operations.