Staff Engineer, ML at K Health

, , -

Full Time

Start Date

Immediate

Expiry Date

18 Apr, 26

Salary

0.0

Posted On

18 Jan, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, Python, Cloud Computing, GCP, AWS, Docker, Kubernetes, PyTorch, Transformers, CI/CD, Model Optimization, System Integration, Code Quality, Collaboration, Infrastructure

Industry

Hospitals and Health Care

Description

Who we are: Founded in 2016, K Health's mission is to deliver accessible, high-quality healthcare at scale. As a leading clinical AI company in primary care, K Health has developed a suite of clinical AI agents that enhance provider efficiency and improve patient outcomes. K Health's virtual primary care platform is enhanced by an AI copilot to complete the initial patient intake, summarizing relevant history from the EMR, and generating “the perfect note” to reduce the time providers spend on basic data collection and non-clinical tasks. Unlike other virtual medicine companies, K Health delivers comprehensive, longitudinal primary care in a virtual setting, enabling our clinicians to be true primary care providers without sacrificing scope of practice or continuity of care. As a venture-backed startup trusted with nearly $400 million in funding and a $900 million valuation as of July 2024, K Health is well-positioned for sustained future growth. We are expanding our partnerships with major health systems (Cedars-Sinai, Hackensack Meridian Health, Hartford HealthCare), enhancing accessibility and quality of care by pairing people with technology. Our providers are credentialed at these renowned academic health systems and adhere to their clinical guidelines, ensuring patient-first, evidence-based care. Fully integrated into Epic, our AI platform enables K Health to operate as an extension of existing healthcare systems, benefiting from a built-in network of specialists and social services to seamlessly serve patients within those communities. Our unique care delivery model enables our providers to deliver the same high-quality, accessible care to a mixed-payer population, including those with commercial insurance, Medicare, and Medicaid. Join us in our mission to deliver smarter, simpler healthcare of the future - today! About the role We are looking for an experienced ML/AI engineer to anchor our ML Platform team. You will lead the effort to productize our Large Language Models, transforming experimental code into robust, efficient services. Your goal is to build the infrastructure that allows our Data Scientists to move fast without breaking production. What you'll be doing: Model Development & Optimization Fine-tuning & Engineering: Develop and fine-tune LLMs/classic models for specific medical tasks (condition detection, dialogue systems) using internal datasets. Research to Production: Partner with Data Scientists to develop experimental code into scalable, production-ready modules. Platform Engineering & Infrastructure Pipeline Orchestration: Build and maintain complex ML workflows using Kubeflow Pipelines (KFP) or similar orchestration tools. Internal Tooling: Develop and manage the internal Python ecosystem—libraries, SDKs, and utilities—that the Data Science team uses for daily development. CI/CD & Automation: Write and maintain CI/CD scripts to automate the testing, versioning, and deployment of machine learning artifacts. Production Standards & Integration System Integration: Work with backend developers to integrate trained models/agents into the core application architecture. Code Quality: Enforce high engineering standards through code reviews, ensuring that research code meets production reliability and maintainability requirements. Requirements Engineering: Translate evolving data science requirements into concrete infrastructure and platform features. What we're looking for: Experience: 10+ years in software engineering with 5+ years in backend/platform roles. Languages: Expert-level Python; proficiency in another language, such as C++, Rust, Java, or Go, is an advantage. Cloud & Infra: 4+ years with GCP (preferred) or AWS, including Docker, Kubernetes, and pipelines (KFP/Vertex). ML Core: Production experience with PyTorch, Transformers, and low-level libraries (CUDA). LLM Stack: Experience with inference optimization (e.g: vLLM/NGC) and fine-tuning (Axolotl/Huggingface). Key Traits: Strong focus on code optimization, system reliability, and collaborative problem-solving. Benefits & Perks: 20 paid vacation days, 18 days sick leave. Hybrid work schedule with team meals and stocked fridges Commuter Benefits Community focused events Pension Plan Stipend per day for food Stock options for every full-time employee Vocational Studies Fund We offer competitive compensation packages based on industry benchmarks for function, level, and geographic location. Offer amounts are determined by multiple factors such as a candidate's experience and expertise. We are proud to be an Equal Opportunity Employer and consider applicants for employment regardless of race, ethnicity, religion, color, national origin, ancestry, disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, sexual orientation, pregnancy, childbirth and breastfeeding, age, citizenship, military or veteran status, or any other class protected by applicable federal, state, and local laws. We’re deeply committed to building teams as diverse as the patients we serve and strive to cultivate an environment where everyone can bring their most authentic self to work. We depend on our differences to make our team stronger, our workplace more dynamic, and our product accessible to all of our users. We are committed to maintaining the integrity of our hiring process and ensuring a safe environment for all candidates. All communication for job offers from K Health will come from email addresses ending in @khealth.com. K Health will never ask you to provide financial information about yourself during the recruitment process. We will never use personal email accounts or other domains for official correspondence. Our official job postings are only listed on our official website and reputable job boards. Be cautious of job offers from sources other than these platforms.

Responsibilities

You will lead the effort to productize Large Language Models, transforming experimental code into robust, efficient services. Your goal is to build the infrastructure that allows Data Scientists to move fast without breaking production.