Sr Software Engineer – Machine Learning

Team: IT

Location: Brazil

Commitment: Full-time

Workplace Type: remote

Accountabilities

• Design and build distributed data pipelines capable of processing large and complex datasets.

• Develop, deploy, and operate machine learning models in production environments.

• Build agent-based AI systems capable of interacting with external services and internal infrastructure.

• Design scalable architectures for data processing, ML training, deployment, and inference pipelines.

• Establish and maintain observability across pipelines, models, and AI agents, including metrics, tracing, and alerting.

• Evaluate different modeling approaches and optimize trade-offs between cost, performance, reliability, and scalability.

• Collaborate with product and customer teams to develop solutions that deliver measurable business impact.

• Take ownership of projects end-to-end, moving rapidly from prototypes and experimentation to production-ready systems.

• Contribute to reliable, well-documented, and maintainable software architectures.

Requirements

• Strong professional experience developing and operating production machine learning systems.

• Solid experience with Apache Spark and SQL in distributed data-processing environments.

• Proven experience working with large, complex datasets and designing scalable data-processing solutions.

• Experience building training, deployment, and monitoring pipelines for machine learning models.

• Experience working with cloud services across data, compute, and machine learning workloads, particularly AWS.

• Strong programming skills in Python and Scala.

• Experience with AWS SageMaker, AWS Bedrock, and Kubernetes is highly relevant.

• Ability to design clear software architectures and produce well-documented technical systems.

• Strong technical communication, collaboration, and problem-solving skills.

• Ability to take strong technical ownership and work effectively across the complete lifecycle of ML systems.

• Experience taking products or technical solutions from 0 to production, particularly in startup or high-growth environments, is a plus.

• Experience with large geospatial datasets and indexing strategies is desirable.

• Experience building AI agents capable of operating at scale is a plus.

• Knowledge of LLM fine-tuning, distillation, or self-hosting is desirable.

• Background in traditional machine learning, particularly with messy datasets and rigorous evaluation methodologies, is a plus.

• Experience with CI/CD, containerization, and infrastructure as code is desirable.

Benefits

• Contractor agreement.

• Compensation paid in USD.

• Fully remote work.

• Opportunity to work on advanced AI and machine learning infrastructure.

• Highly technical environment with significant engineering ownership.

• Opportunity to design and scale systems that move rapidly from concept to production.

• Exposure to distributed systems, machine learning, AI agents, cloud infrastructure, and large-scale data engineering.