Job Description Insight Global is seeking a team of experienced, driven Data Engineer to join an established health technology company sitting San Jose, CA. · Design, develop, and maintain an AI/ML platform to enable the AI to build LLM, Bert, and other models. · Build robust ML training and inference pipelines using ML Flow, Kubeflow, Ray, and Spark. · Ensure the performance, quality, and responsiveness of the models. · Collaborate with cross-functional teams to define, design, and ship new features. · Continuously discover, evaluate, and implement new technologies to maximize development efficiency. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements · Bachelor's degree in computer science, Statistics, Mathematics, or a related field. Advanced degrees are preferred. · Minimum of 5 years of experience in building and maintaining AI/ML platforms using Kubernetes, ML Flow, Kubeflow, Ray, and Spark. · Strong knowledge of machine learning frameworks, libraries, data structures, data modeling, and software architecture. · Good understanding of machine learning algorithms, processes, tools, and platforms. · Experience with cloud services (GCP, AWS, Azure). Cloud-agnostic deployment experience is highly encouraged. · Excellent problem-solving skills and ability to work in a team environment · Experience with startup environments and agile development methodologies. · Strong communication skills with the ability to explain technical concepts to non-technical audiences. · Knowledge of data streaming technologies (e.g., Apache Kafka). · Experience with data visualization tools (e.g., Tableau, Power BI). · Certification in relevant data engineering technologies.