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