Machine Learning Enginee

Role Description This is a part-time remote role for a Machine Learning Engineer. In this position, the engineer will design, build, and deploy machine learning models that support personalized wellness recommendations and habit tracking. Day-to-day responsibilities include exploring wellness-related datasets, developing and optimizing algorithms, implementing and testing neural network architectures, and conducting statistical analyses to validate model performance. The engineer will collaborate with product and wellness experts to translate business and user needs into technical solutions, document workflows, and maintain scalable, reliable ML pipelines suitable for production environments.
Qualifications
Candidates should possess strong Computer Science fundamentals, including data structures, software engineering practices, and familiarity with Algorithms.
Candidates should possess skills in Pattern Recognition and Neural Networks for building and refining predictive and recommendation models.
Candidates should possess a solid foundation in Statistics for data analysis, model evaluation, and experimental design.
Candidates should possess experience with modern machine learning frameworks and tools (e.g., Python, TensorFlow, PyTorch, scikit-learn).
Candidates should possess the ability to work independently in a remote environment, manage part-time hours effectively, and communicate clearly with cross-functional partners.
Relevant qualifications include a degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience; prior work in health, wellness, or behavioral science domains is a plus.

Skills
Machine Learning

Work arrangement
Yes