ML Platform Engineer at K Health

K Health, a telehealth company focused on AI-driven healthcare solutions, is seeking a Machine Learning Platform Engineer. The role involves collaborating with data scientists and DevOps professionals to design and build the infrastructure, ecosystem libraries, and pipelines that power data science initiatives.

Responsibilities:

• Designing, developing, and maintaining machine learning ecosystem libraries.
• Building and managing data science code, Docker images, and Kubeflow Pipelines (KFP).
• Creating and maintaining CI scripts for seamless integration and delivery.
• Conducting code reviews to ensure high-quality standards.
• Collaborating with data scientists to understand and address their needs.
• Working with software developers to integrate machine learning models into production systems.
• Staying current with advancements in machine learning to enhance products and services.

Requirements:

• 5+ years of hands-on industry experience with Python or C++/Rust/Java/Go.
• 3+ years of experience in backend or platform development.
• 2+ years of experience working with cloud platforms such as Google Cloud (preferred), Azure, or AWS, including familiarity with ML workflow frameworks like KFP or Vertex Pipelines.
• Proficiency with Docker.
• Solid experience in ML/AI development.
• Expertise with transformers, PyTorch, CUDA, and other low-level ML libraries.
• Familiarity with inference optimization libraries (e.g., TGI, VLLM, etc.).
• Knowledge of tuning frameworks and libraries (e.g., TorchTune, TRL, Unsloth).
• Familiarity with Kubernetes.
• Strong focus on code quality and optimization.
• Excellent problem-solving skills and a proactive attitude.
• Collaborative mindset with the ability to work closely with cross-functional teams.
• Strong communication and teamwork skills are essential.