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Staff Machine Learning Engineer
Location: Remote (US)
|
Full-Time
Python
Machine Learning
Cloud
GCP
AWS
Azure
Data Science
Staff Engineer
**About Lore:** Lore is a company dedicated to building a new kind of care: a continuous, holistic approach that supports people whether they're flourishing, struggling, or somewhere in between. We focus on preemptive care to address triggers in modern healthcare, which traditionally struggles with fallout. **About The Role:** We are seeking a Staff Machine Learning Engineer to join our team. Our ideal machine learning engineer is hands-on with a track record of taking ideas from concept to implementation. They are comfortable working with cloud platforms, databases and streaming data, developing algorithms and models, setting up and using APIs, and incorporating developed models into larger production software ecosystems. **Responsibilities:** - Continuously explore and define what constitutes a productive conversation in the context of building resilience. - Collaborate with data engineers, software engineers, and fellow machine learning engineers to design, build, and deploy production-grade ML systems. - Champion the integration of emerging machine learning technologies and methodologies tailored to our unique use cases. - Stay abreast of the latest advancements in machine learning, evaluating and applying new techniques to drive innovation. - Articulate complex technical concepts clearly to both technical teams and non-technical audiences. **Requirements:** - MS or higher in Computer/Information Science, Computational Social Science, Mathematics, Statistics, or a related field. - 8+ years of experience in designing, building, and deploying machine learning systems (or a mix of education and a minimum of five years of industry experience). - Strong proficiency in Python, including experience with unit and integration testing, version control, and production-level coding practices. - Familiarity with cloud computing platforms such as GCP, AWS, or Azure. **Nice to Haves:** - Knowledge of network science, including modeling social interactions and community evolution. - Significant experience with and understanding of NLP algorithms and models (e.g. entity extraction and resolution techniques, embeddings, transformers, fine-tuning). - Experience with experimentation platforms including multi-arm and contextual bandits. - Knowledge of and interest in MLOps
Post Date:
July 8, 2025