Role Description This is a part-time remote role for a Machine Learning Engineer at RA Synergy. The Machine Learning Engineer will design, develop, and deploy models that support data-driven decisions in real estate, such as pricing, demand forecasting, and property recommendations. Day-to-day tasks include collecting and preprocessing data, selecting appropriate algorithms, training and validating models, and optimizing performance for production use. The role involves collaborating with product, data, and engineering stakeholders to translate business needs into machine learning solutions, documenting workflows, and maintaining model pipelines. The engineer will also monitor model behavior over time, improve accuracy and robustness, and ensure solutions are scalable and maintainable in a remote, distributed environment.
Qualifications
Strong foundation in Computer Science, including data structures, Algorithms, and software engineering principles.
Proficiency in Pattern Recognition and Neural Networks, with experience applying these methods to real-world datasets.
Solid understanding of Statistics and probabilistic modeling for data analysis, model evaluation, and experimentation.
Hands-on experience with at least one major machine learning framework (e.g., TensorFlow, PyTorch, scikit-learn) and programming languages such as Python.
Experience working with data pipelines, version control (e.g., Git), and cloud or remote development environments.
Ability to interpret business requirements and communicate technical concepts clearly to non-technical stakeholders.
Proven capability to work independently, manage time effectively in a part-time remote setting, and deliver high-quality results.
Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
Prior experience with real estate, geospatial data, or recommendation systems is a plus.

Machine Learning Enginer

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