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You will design, build and operate machine learning systems, large-scale data pipelines and AI agents, taking models from prototype to production with monitoring. The role works across the full ML lifecycle with product and customer teams.
Senior ML Engineer About the Company Our client is a technology company building advanced infrastructure powered by data, machine learning, and AI systems to solve complex problems at scale. They are developing large-scale data pipelines, machine learning models, and agentic systems that enable automated workflows and intelligent decision-making. The team is focused on rapidly taking solutions from concept to production. They are looking for a Senior Software Engineer who wants to work close to the core of the technology stack, building and operating robust AI/ML systems. This position is open to candidates in: Colombia, Argentina, Brazil. What will you do in this role? You will be responsible for designing, building, and operating machine learning systems, large-scale data pipelines, and AI agents that power core product capabilities. This role involves working across the full lifecycle of ML systems — from data ingestion and distributed processing to model deployment and monitoring. Your main responsibilities will include: • Designing and building distributed data pipelines to process large datasets. • Developing and deploying machine learning models in production environments. • Implementing agent-based AI systems that interact with external services and internal infrastructure. • Designing scalable architectures for data processing and ML training pipelines. • Establishing observability for pipelines, models, and agents (metrics, tracing, alerting). • Evaluating modeling approaches and optimizing cost vs. performance trade-offs. • Collaborating with product and customer teams to build solutions that drive business impact. • Iterating quickly from prototype to production-ready systems. This role requires strong technical ownership and the ability to build reliable systems end-to-end. What should you bring? We are looking for engineers with strong experience in production machine learning systems, distributed data processing, and scalable infrastructure. Ideally you have: • Strong experience with Spark and SQL in distributed data environments. • Experience building and deploying machine learning systems in production. • Experience working with large and complex datasets. • Experience designing training, deployment, and monitoring pipelines for ML models. • Experience working with cloud services across data, compute, and ML. • Ability to design clear software architectures and well-documented systems. • Strong technical communication and collaboration skills. Languages: Python, Scala Tools / Frameworks: Spark, AWS (Sagemaker / Bedrock), Kubernetes Nice to Have • Experience building products from 0 to production, especially in startup environments. • Experience working with large geospatial datasets and indexing strategies. • Experience building AI agents that operate at scale. • Experience with fine-tuning, distilling, or self-hosting LLM models. • Background in traditional ML with messy datasets and strong evaluation methodologies. • Experience with CI/CD, containerization, and infrastructure as code. What you will receive • Contractor agreement • Compensation in USD • Fully remote work • Opportunity to work on cutting-edge AI and ML infrastructure • Highly technical environment with strong engineering ownership • The chance to build and scale systems that move from idea to production quickly Submit your resume and join a process that can change your life. Best regards, T-mapp Team
Posted Nov 9, 2026
