Machine Learning Engineer

REDLEO SOFTWARE INC.; A distancia; MXN 1,606,000 - 2,143,000; Jornada completa

Descripción de la vacante

A leading software company seeks an experienced AI/ML Developer Lead/MLOps Engineer to drive innovation in predictive analytics solutions for operational excellence in industrial settings. The ideal candidate will be instrumental in architecting scalable AI/ML solutions, implementing best practices, and managing real-time IoT data pipelines using advanced technologies and programming languages. This remote role offers the chance to create impactful AI-driven solutions across industries.

Formación

• Proven experience in architecting AI/ML solutions for predictive maintenance and operational optimization.
• Strong understanding of Industrial IoT (IIoT) and streaming analytics.
• Experience in implementing MLOps best practices in production environments.

Responsabilidades

• Architect and lead development of scalable AI/ML solutions.
• Develop enterprise AI/ML strategy based on business priorities.
• Design and implement data pipelines for IoT data processing.

Conocimientos

AI/ML Solutions Architecture

Data Pipeline Development

Deep Learning Techniques

Python Programming

MLOps Best Practices

Statistical Modeling

Natural Language Processing

Herramientas

TensorFlow

Kafka

Snowflake

PyTorch

Descripción del empleo

Brand New Role 2026

Role: AI/ML Developer Lead / MLOps Engineer

Type: REMOTE

Anywhere from Mexico- Remote

English & Spanish

collects high‑frequency IoT data from its rock‑processing equipment in real time using Kafka, with all streaming data ingested and stored in Snowflake. The company is seeking an experienced Machine Learning Leader to design, architect, and implement real‑time predictive analytics solutions that drive operational excellence across industrial operations.

Key Responsibilities

• Architect and lead development of scalable, high‑performance AI/ML solutions for predictive maintenance, anomaly detection, and operational optimization across industrial machinery.
• Develop an enterprise AI/ML strategy aligned with business priorities, with emphasis on Industrial IoT (IIoT), streaming analytics, and edge‑based inference.
• Design and implement robust data pipelines for ingesting, transforming, and processing real‑time IoT data using Kafka, Snowflake, and related technologies.
• Build and optimize advanced ML models, applying deep learning, statistical modeling, reinforcement learning, NLP, and other AI techniques as appropriate.
• Develop production‑grade ML models using Python, TensorFlow, PyTorch, and modern ML libraries.
• Implement MLOps best practices, including CI/CD pipelines, model versioning, automated testing, monitoring, and model lifecycle governance.
• Deploy ML solutions into production, ensuring scalability, reliability, and low‑latency performance within real‑time environments.
• Translate complex business problems into AI‑driven solutions, working closely with engineering and operational teams to deliver measurable impact.
• Develop algorithms and techniques to maximize model accuracy, reliability, resilience, and real‑world performance in dynamic industrial environments.

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