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.

In this role, you will act as a key technical driver, bridging the gap between data science and production systems. You will design, build, and deploy scalable machine learning solutions, ensuring models operate reliably and efficiently within business environments. The position requires deep technical expertise in programming, cloud platforms, and data engineering, along with strong problem-solving and analytical skills. You will collaborate closely with data scientists, engineers, and stakeholders to deliver impactful solutions that unlock the value of data. This is an opportunity to work in a fast-paced, innovative environment where creativity, autonomy, and professional growth are highly encouraged.

Accountabilities

Design and implement environments that allow data scientists to develop and test models effectively.
Extract, transform, and prepare data from multiple sources for analytical and machine learning purposes.
Define deployment strategies and infrastructure for production-ready ML models, ensuring scalability, reliability, and integration with business systems.
Partner with data scientists to operationalize machine learning models, including validation, QA testing, and monitoring in production.
Develop robust data pipelines and ensure high-quality delivery across the lifecycle of ML solutions.
Collaborate with cross-functional teams to provide technical guidance, optimize processes, and recommend the most suitable tools and technologies.

Requirements

Bachelor’s degree in Computer Engineering, Data Science, or a related field (Master’s preferred).
Minimum 4 years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer.
Hands-on experience deploying data science and ML models in production environments.
Strong programming skills in Python, Scala, Java, or similar languages.
Expertise in SQL and building/optimizing distributed queries.
Familiarity with ML libraries and frameworks such as TensorFlow, Keras, scikit-learn, h2o.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Systems-level knowledge in cloud architecture, Linux, storage systems, and data platforms (AWS, Azure, GCP, Databricks).
Experience with APIs and web frameworks (Flask, Django, Spring) and full software development lifecycle practices.
Excellent communication, analytical, and problem-solving skills, with experience collaborating with internal or external customers.

Preferred: Hands-on experience with additional data technologies (HBase, Impala, Solr, Kudu, Streamsets, NiFi, ElasticSearch), cloud ML platforms (AWS SageMaker, MLFlow), and contributions to open-source projects.

Benefits

Remote-first work environment with flexibility across Latin America.
Competitive compensation with comprehensive benefits and perks.
Generous PTO and 10 national holidays.
Collaborative, award-winning culture emphasizing autonomy, creativity, and transparency.
Opportunities for accelerated professional development through advanced training and certifications.
Inclusive and diverse workplace committed to employee well-being and growth.

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 three 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.

This 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 offering the position. The final decision and next steps (such as interviews or assessments) are made by their internal hiring team.

Thank you for your interest!

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