Machine Learning Engineer

TL;DR

Machine Learning Engineer: Design, build, and deploy machine learning models and pipelines for data-driven products with an accent on scalable ML infrastructure and production deployment. Focus on developing reliable, high-performing ML solutions, including deep learning and large language models, and collaborating across teams to translate business needs into technical implementations.

Location: Remote (Mexico)

Company

Tech Holding is a full-service consulting firm delivering high-quality solutions with a foundation of deep expertise, integrity, and transparency, serving clients from startups to Fortune 50 companies.

What you will do

• Design, develop, and deploy machine learning models to solve business problems across large-scale datasets.
• Build and optimize ML pipelines for data preparation, training, and inference.
• Collaborate with data and software engineers to develop scalable ML infrastructure.
• Research and implement modern ML techniques including deep learning and large language models.
• Translate business requirements into technical solutions with cross-functional teams.
• Monitor model performance, conduct experiments, and improve accuracy and reliability.

Requirements

• Must have 5+ years of professional experience in machine learning engineering or related roles.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience deploying ML models in production and working with large-scale data pipelines.
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.
• Bachelor's or Master's degree in Computer Science, Machine Learning, or related field (or equivalent experience).
• Location: Remote work from Mexico.

Nice to have

• Experience with NLP, computer vision, recommendation systems, or other applied ML domains.
• Familiarity with model deployment, experiment tracking, and monitoring tools.
• Experience with distributed systems and scalable ML infrastructure.
• Exposure to transformer architectures, embeddings, or large language models.
• Experience in fast-paced startup or product-driven environments.

Culture & Benefits

• Remote work opportunity.
• Equal opportunity employer committed to diversity and inclusion.