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

In this role, you will lead the design and deployment of advanced machine learning solutions, shaping the infrastructure and workflows that bring data science models into production. You will work closely with data scientists and engineering teams to ensure models are robust, scalable, secure, and maintainable. This position combines technical leadership with hands-on implementation, spanning data pipelines, model deployment, and operationalization. You will have the opportunity to influence the architecture, recommend technologies, and deliver impactful solutions across diverse industries. The environment is fully remote, collaborative, and focused on innovation, offering a platform to grow your expertise in machine learning and cloud technologies while driving real-world business outcomes.

Accountabilities

Design and implement environments for data scientists to build and test machine learning models.
Develop robust data pipelines to extract, transform, and load data from multiple sources (e.g., RDBMS, Kafka, DWH).
Define model deployment strategies, including infrastructure planning, QA testing, and production rollout.
Collaborate with teams to ensure model solutions are scalable, secure, and maintainable.
Transform raw data into actionable insights by working with data scientists to format and deploy models.
Provide thought leadership on technology choices and solution architecture from application layer to infrastructure.
Maintain high standards of software quality through operational testing, monitoring, and validation.
Support ongoing maintenance and optimization of deployed machine learning solutions.

Requirements

Bachelor’s degree in Computer Science or a related field (Master’s preferred).
6+ years of experience as a Machine Learning Engineer, Software Engineer, or Data Engineer.
Proven experience deploying machine learning models in production.
Proficiency in Python, Scala, Java, or similar programming languages.
Hands-on experience with big data ecosystems (e.g., Spark, Snowflake, Databricks).
Strong SQL skills with the ability to debug, optimize, and query distributed databases.
Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
Experience developing APIs and web applications (e.g., Flask, Django, Spring).
Solid understanding of network/cloud architecture, operating systems, and storage systems.
Excellent communication and presentation skills to engage with internal and external stakeholders.
Knowledge of full software development lifecycle, including design, documentation, testing, and deployment.

Nice-to-Have:

Master’s degree in data science or related field.
Experience with MLflow, AWS SageMaker, Azure ML, or other ML operational tools.
Familiarity with AI/ML libraries like TensorFlow, Keras, scikit-learn, h2o.
Open-source contributions or relevant side projects.
Experience building enterprise-scale ML models.

Benefits

Fully remote-first work environment across Latin America.
Casual, award-winning company culture emphasizing autonomy and creativity.
Competitive salary and comprehensive benefits package.
Generous paid time off, including holidays.
Accelerated learning through professional development, certifications, and training programs.
Inclusive, diverse, and supportive workplace valuing collaboration and transparency.

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 for 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, it is shared directly with the hiring company, whose internal team will make the final decision and contact selected candidates for the next steps.

Thank you for your interest!

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