This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Machine Learning Engineer in Latin America.

This role offers a unique opportunity to lead the development and deployment of machine learning solutions that directly impact business outcomes. You will work closely with product and engineering teams to design scalable, high-performance models and pipelines, contributing to the technical vision of the organization. The position combines hands-on engineering with strategic thinking, allowing you to shape ML architectures, mentor junior team members, and influence key technical decisions. You will engage with large-scale datasets, cutting-edge ML frameworks, and cloud platforms to solve real-world challenges while advancing both your expertise and the company’s capabilities. Remote-first flexibility ensures you can deliver impact from anywhere in the region while collaborating effectively with global teams.

Accountabilities

Lead the design, development, and deployment of machine learning and deep learning models to solve complex business problems.
Develop and maintain clean, scalable, and efficient code following industry best practices.
Analyze large datasets to extract actionable insights and inform decision-making.
Employ advanced ML methodologies and frameworks to create robust, production-ready models.
Influence technical direction and take ownership of critical components of systems and solutions.
Collaborate with product, engineering, and business stakeholders to deploy data-driven solutions.
Mentor junior engineers, fostering domain expertise and best practices within the team.
Contribute to technical leadership through publications, patents, or knowledge sharing initiatives.

Requirements

5+ years of industry experience in applied machine learning.
Master’s degree or PhD in Computer Science, Machine Learning, or a related field.
3+ years building, deploying, and managing ML and deep learning models at scale in production.
Deep understanding of ML best practices: feature engineering, training/serving pipelines, A/B testing, and experiment design.
Experience with algorithms and techniques such as gradient boosting, deep neural networks, optimization, and regularization.
Proven experience in one or more domains: personalization, recommender systems, computer vision, fraud detection, marketing, or price estimation.
Strong programming skills in Python and SQL; proficiency with scientific libraries (numpy, pandas) and ML frameworks (Scikit-Learn, TensorFlow, Keras, PyTorch).
Experience with big data tools and platforms (Apache Beam, Spark, Kafka).
Knowledge of cloud technologies (AWS, GCP, Azure) and production ML workflows.
Excellent problem-solving skills, leadership experience, and ability to mentor team members.

Preferred: PhD in CS/ML/AI, experience applying ML in retail or e-commerce, familiarity with MLOps pipelines, and demonstrated impact through high-quality, production-ready models.

Benefits

Fully remote work across Latin America with flexible working hours.
Competitive salary with equity opportunities.
Opportunity to work on impactful, real-world ML projects at scale.
Professional growth and mentorship in a collaborative, high-performance environment.
Exposure to cutting-edge ML technologies, large datasets, and cloud-native architectures.
Career development opportunities through technical leadership and publications.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

#LI-CL1

Newsletter