Clover Health - Senior Machine Learning Engineer

• You want to create impact with your work by finding machine learning-driven insights in the data to unlock value and improve health outcomes for real people. • impact • You are comfortable acting autonomously in ambiguous and changing environments. • autonomously • You value collaboration and feedback. You can communicate technical vision in clear terms— to your teammates and across the technology team more broadly. You are willing and able to help your teammates grow by demonstrating best practices, providing (and receiving) respectful and constructive feedback, and disclosing your unique insights with everyone. • collaboration • You enjoy working in a fluid environment, defining priorities that adapt to our larger goals. You can bring clarity to ambiguity while remaining open-minded to new information that might change your mind. • fluid environment • You are not hesitant to jump in to help fix things that are broken and you are encouraged to make sustainable systems. You are happy to fill in the gaps to reach a goal where necessary, even if it does not always fit your job description. • sustainable systems • You have a genuine interest in what good technology can do to help people and have a positive attitude about tackling hard problems in an important industry. • positive attitude • You should get in touch if: • You have 5+ years of experience in Machine Learning Engineering roles in technology enabled companies. Healthcare experience preferred but not required. • You have experience with Python, Python data science libraries (numpy, pandas, sklearn, tensorflow, pytorch, etc.), and deploying Python apps into production environments. • You have experience with Natural Language Processing and/or LLMs. • You have a solid foundation in feature engineering, feature selection, and machine learning techniques. • You have experience interpreting, modifying, and debugging the inputs and outputs of production ML/NLP/LLM models. • You have both built and refactored complex distributed systems, especially ML/NLP/LLM systems. • You have scaled the impact of other engineers and data scientists through mentorship, development of reusable libraries, and documentation.