Machine Learning Engineer II

Summary

Join Clover's Counterpart Health team as a Machine Learning Engineer II and help build a revolutionary healthcare business. You will create, debug, and improve production ML models, design and implement reliable ML platforms, and build tools to translate insights into action. Collaboration with Data Science and Engineering teams is crucial to ensure the ML platform delivers real value. The ideal candidate possesses 3+ years of experience in Machine Learning Engineering, proficiency in Python and related libraries, and a strong foundation in AI techniques. This role offers opportunities for growth and impact, working in a supportive and collaborative environment.

Requirements

• You have 3+ years of experience in Machine Learning Engineering or related 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 a solid foundation in feature engineering, feature selection, and AI techniques
• You have experience interpreting, modifying, and debugging the inputs and outputs of production ML models
• You have both built and refactored parts of distributed systems, especially ML systems

Responsibilities

• Create, debug, interpret and improve production ML models
• Design, implement and validate pieces of our high-reliability, distributed platforms for ML
• Build the tools and validation processes that help Counterpart translate insights into action at scale
• Use existing commercial and open source tools to create a robust production platform
• Work closely with Counterpart’s Data Science and Engineering teams to ensure that the ML platform is providing real value
• Document, iterate, and provide tutorials to ensure Data Scientists and Engineers are able to use your tools easily

Preferred Qualifications

Healthcare experience

Benefits

• Competitive base salary and equity opportunities
• Performance-based bonus program
• Regular compensation reviews
• Comprehensive group medical coverage that include coverage for hospitalization, outpatient care, optical services, and dental benefits
• No-Meeting Fridays
• Company holidays
• Access to mental health resources
• A generous annual leave policy
• Remote-first culture
• Learning programs
• Mentorship
• Professional development funding
• Regular performance feedback and reviews
• Reimbursement for office setup expenses
• Flexibility to work from home, enabling collaboration with global teams
• Paid parental leave for all new parents