GenAI & ML Engineer — Remote, Production-Ready AI

Jobgether; Mexico; On-site; PHP 6,196,000 - 7,435,000; Full time

Benefits offered by this job

Remote working model

Full-time position

Exposure to GenAI and MLOps tech

Job summary

Jobgether is listing a position on behalf of a partner company seeking an AI/ML & Forward Deployed Engineer based in Mexico. The role focuses on building and deploying high-impact AI, ML, and GenAI solutions from concept to production, blending software engineering with ML and MLOps practices.

You will work on LLMs, RAG pipelines, NLP, forecasting, anomaly detection, and end-to-end AI lifecycle management, with emphasis on security, governance, observability, and data quality in production

Qualifications

• 8+ years of professional software engineering or technical engineering experience.
• Strong hands-on experience in Machine Learning and AI/ML Engineering.
• Advanced Python development skills and practical experience with deep learning and machine learning techniques.
• Experience with NLP, forecasting, classification, regression, and anomaly detection.
• Proven experience building GenAI applications using LLMs and Retrieval-Augmented Generation (RAG) architectures.
• Strong understanding of embeddings, retrieval tuning, reranking, prompt engineering, and AI/LLM evaluation methodologies.
• Solid knowledge of MLOps and LLMOps principles and practices across the AI development lifecycle.
• Hands-on experience with Docker, Kubernetes, and CI/CD technologies for production deployments.

Responsibilities

• Design, develop, and deploy machine learning, AI, and GenAI solutions from proof of concept through production.
• Build and optimize ML models and applications covering deep learning, NLP, forecasting, classification, regression, and anomaly detection use cases.
• Develop production-grade GenAI applications using LLMs, RAG pipelines, embeddings, retrieval optimization, reranking, and prompt engineering.
• Design and implement AI evaluation frameworks to assess model quality, reliability, relevance, and performance.
• Build scalable AI services and integrations using REST and gRPC APIs as well as event-driven architectures.
• Establish and maintain MLOps and LLMOps practices covering deployment, automation, versioning, monitoring, and lifecycle management.
• Containerize and orchestrate AI applications using Docker and Kubernetes and integrate them into robust CI/CD pipelines.
• Implement model monitoring, drift detection, performance tracking, and processes for continuous model improvement.
• Ensure AI solutions meet enterprise requirements for data quality, governance, security, role-based access control, encryption, and auditability.
• Collaborate with business and technical stakeholders to translate business needs into practical technical solutions.
• Support solutions through production operations, troubleshooting, optimization, and ongoing improvements.
• Apply strong engineering practices to ensure AI systems are scalable, secure, observable, maintainable, and aligned with business objectives.

Skills

Python

Machine Learning

NLP

GenAI

LLMOps

MLOps

REST APIs

Docker

Tools

Docker

Kubernetes

CI/CD

REST

gRPC

Job description

Jobgether is listing a position on behalf of a partner company seeking an AI/ML & Forward Deployed Engineer based in Mexico. The role focuses on building and deploying high-impact AI, ML, and GenAI solutions from concept to production, blending software engineering with ML and MLOps practices.

You will work on LLMs, RAG pipelines, NLP, forecasting, anomaly detection, and end-to-end AI lifecycle management, with emphasis on security, governance, observability, and data quality in production