Engenheiro de Dados - ML Especialista in Brazil, Indiana at Jobgether
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Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Engenheiro de Dados - ML Especialista in Brazil.
This role is a high-impact technical position focused on designing, building, and scaling data infrastructure that powers advanced Machine Learning solutions in production environments. You will act as a key architect of data pipelines, ensuring that data is reliable, accessible, and optimized for both training and inference of ML models. Working at the intersection of data engineering and machine learning, you will help define the standards for MLOps and data strategy within a collaborative and innovation-driven engineering culture. The position involves close interaction with data scientists and engineering teams to enable robust, scalable AI systems. You will also play a strategic role in mentoring peers and shaping best practices for data workflows and ML operations. This is a hands-on, leadership-oriented role where your work directly impacts model performance and business outcomes at scale.
- Design, build, and maintain scalable data pipelines (ETL/ELT) to support Machine Learning workflows in production environments.
- Ensure data quality, integrity, and availability across all stages of ML model training and inference processes.
- Develop and optimize big data architectures using technologies such as Apache Spark, Airflow, and related frameworks.
- Implement and improve MLOps practices, including model versioning, monitoring, retraining, and deployment automation.
- Collaborate with data scientists and engineering teams to support end-to-end development of machine learning models.
- Define and evolve data engineering and ML infrastructure strategies, ensuring scalability and performance.
- Mentor team members and contribute to technical leadership in data engineering and MLOps best practices.
- Strong experience in Machine Learning concepts and end-to-end model development.
- Advanced expertise in data engineering, including ETL/ELT pipeline design and optimization.
- Proficiency in Python and data/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Hands-on experience with big data ecosystems, including data lakes and data warehouses.
- Solid knowledge of MLOps practices such as model deployment, monitoring, versioning, and retraining pipelines.
- Experience working with distributed processing frameworks such as Apache Spark and workflow orchestration tools like Airflow.
- Strong analytical thinking, problem-solving ability, and experience working in complex data environments.
- Ability to mentor others and contribute to technical leadership in multidisciplinary teams.
- Meal or food allowance.
- Discounts on educational programs, universities, and language courses.
- Access to an internal learning platform with free certified courses.
- Mentoring and professional development programs.
- Medical and dental assistance plans.
- Wellness and healthcare benefits, including access to discounted medical services.
- Travel and partner discount programs.
- Pet care benefits through corporate partnerships.