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Brasil
Remote only
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr Software Engineer – Machine Learning based in Brazil.
This is a senior engineering opportunity focused on building production-grade machine learning and AI infrastructure at scale.
You will work across distributed data pipelines, ML systems, AI agents, deployment, and observability.
The role covers the full lifecycle of intelligent systems, from data ingestion and experimentation through production and monitoring.
You will have significant technical ownership and contribute to architectures designed for reliability, scalability, and performance.
The environment is highly technical, fast-moving, and oriented toward turning prototypes into robust production solutions.
You will collaborate with product and customer-facing teams to translate complex technical challenges into impactful solutions.
This role is ideal for an engineer who enjoys solving large-scale problems and working close to the core of AI/ML technology.
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.
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.
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.
