Plenful - Machine Learning Engineer
Requirements
• Have worked with Large Language Models (LLMs), retrieval-augmented generation (RAG), embeddings, or agentic AI systems • Have fine-tuned foundation models or worked with prompt engineering techniques • Are familiar with ML infrastructure tools such as MLflow, Weights & Biases, Airflow, Kubeflow, or SageMaker • Have experience with vector databases and semantic search technologies • Have healthcare, pharmacy, or health tech experience • Have worked in a startup or other fast-paced environment • Technologies you'll likely work with: Python, PyTorch, TensorFlow, Scikit-learn, SQL, PostgreSQL, Docker, Kubernetes, AWS, GitHub Actions, REST APIs, vector databases, and LLM APIs (OpenAI, Anthropic, etc.) • Technologies you'll likely work with:
Responsibilities
• 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, and bring practical innovations into our platform • You May Be a Fit If • You have 5+ years of professional software engineering or machine learning engineering experience • You have a Bachelor's degree in Computer Science, Machine Learning, Engineering, Mathematics, or a related technical field (or equivalent practical experience) • You have strong programming experience in Python • You've built and deployed machine learning models into production environments • You have a solid understanding of supervised and unsupervised learning techniques • You're familiar with modern ML infrastructure — 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, or Qdrant for RAG pipelines) • You've built data pipelines using SQL and distributed data processing tools • You're familiar with cloud platforms such as AWS, GCP, or Azure • You've deployed containerized applications using Docker and Kubernetes • You have a strong grasp of software engineering fundamentals — testing, version control, and CI/CD • You communicate well and collaborate easily across technical and non-technical teams
Benefits
• 🚀 Mission-Driven, World-Class Team — Join an exceptional group of professionals aligned around a meaningful mission and committed to making an impact • Mission-Driven, World-Class Team • 📈 Opportunities for Growth — Strengthen your expertise through collaboration with experienced, high-performing leaders across the organization • Opportunities for Growth • 🏢 Flexible Hybrid Work Environment — We're remote-first, with meaningful office presence in San Francisco and New York. R&D roles follow a hybrid model, with two days per week in our San Francisco office • Flexible Hybrid Work Environment • 🏥 Healthcare Coverage — Full medical, dental, and vision insurance for you and participation for your family • Healthcare Coverage • 💰 401(k) with Company Match — Plenful matches 50% of your first 3% contributed • 401(k) with Company Match • 📊 Equity — Every full-time employee shares in our success • Equity • 🌴 Unlimited PTO — Take the time you need, when you need it • Unlimited PTO • 🍽️ Daily Lunch Stipend — $100/week to cover your midday meals • Daily Lunch Stipend • 💪 Wellness Stipend — $100/month to support your health and well-being • Wellness Stipend • 🚇 Commuter Benefits — $100/month for SF and NYC-based employees • 👶 Parental Leave — Paid leave to support growing families • Parental Leave
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