Senior Machine Learning Engineer

About the role

You will design, implement, and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs that directly support Clover Health's primary care mission. You will create, debug, interpret, and improve production machine learning and natural language processing models to predict avoidable adverse events and drive proactive care. You will build the tools and validation processes that help Clover translate insights into action at scale across a diverse organization. You will use existing commercial and open source tools to create a robust production platform that is reliable, maintainable, and performant. You will work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is providing real, measurable value to beneficiaries and clinicians. You will document, iterate, and provide tutorials to ensure Data Scientists and Engineers can use your tools easily and effectively to advance the platform.

Key facts

What you'll do

• Design, implement and validate high-reliability, distributed platforms for machine learning, natural language processing, and LLMs that support clinical decision-making.
• Create, debug, interpret and improve production machine learning and natural language processing models with a focus on scalability and robustness.
• Build the tools, pipelines, and validation processes that help Clover translate data insights into action at scale across care teams.
• Use existing commercial and open source tools to create a cohesive, robust production platform that integrates smoothly into existing infrastructure.
• Work closely with Clover's Data Science and Engineering teams to ensure that the ML/NLP/LLM Platform is aligned with real-world needs and delivers measurable impact.
• Translate complex model behavior into clear documentation, tutorials, and best practices so that Data Scientists can use tools effectively.
• Collaborate with cross-functional stakeholders to define requirements, prioritize work, and adapt to evolving goals in a fluid environment.
• Take ownership of the end-to-end lifecycle of machine learning systems, from experimentation and prototyping through deployment, monitoring, and iterative improvement.
• Champion sustainable systems and fill gaps where needed to ensure reliable operation and continuous impact on health outcomes.
• Contribute to the expansion of the Machine Learning/Natural Language Processing/LLM capabilities of the Data Platform through clean, maintainable, and well-tested code.
• Mentor and scale the impact of other engineers and data scientists by developing reusable libraries, clear documentation, and knowledge-sharing practices.
• Demonstrate strong judgment when making tradeoffs between model complexity, performance, reliability, and delivery timelines in a healthcare context.
• Engage with real-world data and clinical workflows to ensure models are practical, interpretable, and aligned with provider needs.
• Drive experiments from idea through production, analyzing results and refining approaches based on observed outcomes and stakeholder feedback.

Requirements

• You have 5+ years of experience in Machine Learning Engineering roles in technology-enabled companies, with healthcare experience preferred but not required.
• You have demonstrated experience with Python, Python data science libraries (numpy, pandas, sklearn, tensorflow, pytorch, etc.), and deploying Python applications into production environments.
• You have hands-on experience with Natural Language Processing and/or LLMs, including training, fine-tuning, and inference optimization.
• You possess a solid foundation in feature engineering, feature selection, and machine learning techniques that apply to real-world, high-stakes problems.
• You have experience interpreting, modifying, and debugging the inputs and outputs of production ML/NLP/LLM models to ensure correctness and safety.
• You have built and refactored complex distributed systems, with a strong track record in ML/NLP/LLM systems in production.
• You have scaled the impact of other engineers and data scientists through mentorship, development of reusable libraries, and clear, up-to-date documentation.
• You are comfortable acting autonomously in ambiguous and changing environments while maintaining clarity and focus on the overall mission.
• You value collaboration and feedback, communicating technical vision clearly to both technical and non-technical stakeholders.
• You are not hesitant to jump in and fix issues, taking responsibility for sustainable systems and filling gaps to reach shared goals.
• You have a genuine interest in how good technology can improve people's lives and a positive attitude toward tackling hard problems in an important industry.
• You are able to work fully remotely from within the United States in accordance with Clover Health policies.

Nice to have

• Experience contributing to open source projects or building internal tools that were adopted by multiple teams.
• Familiarity with regulated healthcare environments and considerations for data privacy and compliance.
• Experience with MLOps platforms, monitoring, and observability for production ML systems.

Practical notes

This role is full-time and remote within the United States. Applicants must be eligible to work in the United States without sponsorship for this position.