Senior Software Engineer (Machine Learning )
Remote · Brasília, Federal District, Brazil or BR
Job Summary
Senior Software Engineer (Machine Learning) to architect, build, and deploy high-performance machine learning systems across the ML lifecycle. The role requires building scalable, production-grade code and real-time inference APIs, managing offline/online feature pipelines, and ensuring low latency and high throughput. You will work on end-to-end ML workloads—from data processing of massive bidstream/event data to training and deploying models (tree-based and neural networks) with MLOps pipelines, automated retraining, versioning, and monitoring. The position emphasizes applying rigorous evaluation, leakage prevention, and robust experimentation (A/B tests) to production-grade ML systems, with a focus on scalable data engineering, feature pipelines, and deployment in high-scale environments.
Required Qualifications
- 5–8+ years of experience as a Machine Learning Engineer or Software Engineer focusing on ML systems
- Production Engineering Skills: Strong software engineering fundamentals (OOP, data structures, algorithm design). Expert-level Python and strong proficiency in a compiled or high-performance language (e.g., C++, Java, Scala, Go, or Rust).
- ML Systems & Serving: Deep experience deploying machine learning models into highly concurrent, low-latency production environments (APIs, microservices, Triton Inference Server, custom containers).
- Distributed Computing: Hands-on experience with big data processing (Apache Spark, Kafka, Flink) and complex SQL queries.
- Core ML & Deep Learning: Proven track record of shipping both tree-based models and neural networks (PyTorch/TensorFlow) to production.
- Statistics & Experimentation: Solid grasp of statistics, hypothesis testing, and rigorous A/B experiment design.
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