Job Opportunities API

ABOUT PLENFUL Plenful is on a mission to transform healthcare operations from the inside out. Fresh off our $50M Series B and backed by Notable Capital, Bessemer Venture Partners, TQ Ventures, Susa/Kivu Ventures, and other leading investors, we’re building the category-defining AI workflow automation platform that healthcare teams rely on to operate smarter, faster, and more efficiently. Our technology empowers healthcare operators across hospital and health systems, pharmacies and payors to eliminate manual work, reduce administrative burden, and improve compliance, all while unlocking critical revenue to fund programs for their in-need patient populations. Built by healthcare operators for healthcare operators, Plenful is driven by a deep understanding of the challenges facing today’s care teams. We’re passionate about equipping healthcare workers with world-class tools that deliver real, measurable impact, and we’re proud to serve 90+ leading health systems across the country. If you’re excited to help shape the future of healthcare, we’d love to meet you. Apply now to join our growing team. We're looking for a Machine Learning Engineer to help design, build, and deploy production-grade machine learning systems that power the next generation of Plenful's AI platform. You'll partner closely with software engineers, product managers, and data teams to develop models and intelligent services that automate healthcare workflows, improve operational efficiency, and create exceptional user experiences. This is an engineering-focused role where you'll own the end-to-end lifecycle—from experimentation to production deployment and ongoing model performance. If you're excited about applying modern machine learning techniques in a fast-moving startup environment where your work directly impacts customers, we'd love to meet you. WHAT YOU'LL DO - Design, build, and deploy machine learning models into production. - Develop scalable ML pipelines for training, evaluation, monitoring, and inference. - Build intelligent services using modern NLP, LLM, classification, recommendation, and prediction techniques where appropriate. - Collaborate with Product and Engineering to translate customer problems into ML solutions. - Improve model performance through experimentation, feature engineering, and evaluation. - Work with structured and unstructured datasets to develop production-ready features. - Implement monitoring, observability, and retraining strategies to maintain model quality. - Optimize model latency, scalability, and infrastructure costs. - Contribute to architecture discussions and engineering best practices. - Stay current with advancements in machine learning and AI, bringing practical innovations into our platform. WHAT WE'RE LOOKING FOR REQUIRED QUALIFICATIONS - 5+ years of professional software engineering or machine learning engineering experience. - Bachelor's degree in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field (or equivalent practical experience). - Strong programming experience in Python. - Experience building and deploying machine learning models into production environments. - Solid understanding of supervised and unsupervised learning techniques. - Familiarity with modern ML infrastructure spanning classical MLOps (MLflow, Weights & Biases, Airflow) and LLMOps (LangFuse/LangSmith for tracing, Ragas/Braintrust for evaluation, vLLM/BentoML for serving, and a vector database such as Pinecone/Weaviate/Qdrant for RAG pipelines). - Experience building data pipelines using SQL and distributed data processing tools. - Familiarity with cloud platforms such as AWS, GCP, or Azure. - Experience deploying containerized applications using Docker and Kubernetes. - Strong understanding of software engineering fundamentals, testing, version control, and CI/CD. - Excellent communication skills with the ability to collaborate