Machine Learning Engineer

About the role

Plenful is an AI workflow automation company for healthcare operations that recently secured 50 million dollars in Series B funding. You will develop and maintain production-ready machine learning systems that automate administrative tasks for over 90 health systems, pharmacies, and payors.

Key facts

What you'll do

• Architect and launch machine learning models using NLP, LLMs, classification, and predictive modeling.
• Build and manage scalable pipelines for model training, inference, monitoring, and automated retraining.
• Prepare and integrate structured and unstructured healthcare data for production features.
• Work with product and engineering teams to convert operational healthcare challenges into technical ML solutions.
• Evaluate and integrate new AI research to improve platform performance and architecture.

Requirements

• 5+ years of professional experience in software or machine learning engineering.
• Bachelor degree in Computer Science, Mathematics, Engineering, or an equivalent technical field.
• Proficiency in Python and SQL.
• Experience with containerized environments using Docker and Kubernetes.
• Background in deploying ML models to production and managing distributed data pipelines.
• Familiarity with MLOps tools like MLflow, Weights & Biases, and Airflow.
• Familiarity with LLMOps tools including LangFuse, LangSmith, Ragas, Braintrust, vLLM, and BentoML.
• Experience with vector databases such as Pinecone, Weaviate, or Qdrant.
• Knowledge of cloud platforms, REST APIs, and CI/CD workflows.

Nice to have

• Practical experience with RAG, embeddings, fine-tuning, or agentic AI.
• Skills in semantic search and prompt engineering.
• Previous work history in health tech, pharmacy, or healthcare.
• Experience operating within high-growth startup environments.

Skills & tools

• Languages and Frameworks: Python, PyTorch, TensorFlow, Scikit-learn
• Data: SQL, PostgreSQL, Pinecone, Weaviate, Qdrant
• Infrastructure: AWS, Docker, Kubernetes, GitHub Actions
• LLM Ecosystem: OpenAI, Anthropic, LangFuse, LangSmith, vLLM, BentoML

Practical notes

• This role is hybrid, requiring 2 days per week in the San Francisco office.
• Compensation includes salary and equity.
• Benefits include a 401(k) with a 50 percent match on the first 3 percent of contributions, plus full medical, dental, and vision insurance.
• Perks include unlimited PTO, paid parental leave, a 100 dollar weekly lunch stipend, a 100 dollar monthly wellness stipend, and a 100 dollar monthly commuter stipend.