At Lendbuzz, we believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, we’ve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.
We are seeking a skilled and motivated Software Engineer focused on Large Language Model (LLM) applications to join our Machine Learning team. In this role, you will help design, build, and optimize next-generation conversational agent technologies. You will collaborate closely with ML researchers and product teams to ship high-impact features and own key components of our conversational AI stack. This position reports to the ML Research Scientist.
This is a hybrid position based in Boston, MA and requires 3 days onsite.
Key Responsibilities:
Software engineering for LLM-powered conversational agents, with an emphasis on practical implementation, reliability, and user experienceEvaluate, fine-tune, and deploy LLM-based models and pipelines using REST APIs and internal microservicesImplement prompt engineering, retrieval-augmented generation (RAG), tool-use pipelines, and conversation orchestration logicInvestigate and integrate emerging technologies, particularly in real-time voice, streaming, and multi-modal interactionAnalyze model outputs, user interactions, and system performance to drive iterative improvementsBuild and maintain high-quality datasets, including data cleaning, preprocessing, labeling workflows, and benchmarking for NLP tasksOwn data quality, ensuring accuracy, reproducibility, and reliability across the data lifecycleCollaborate with ML, backend, and product teams on deployment best practices, monitoring, and scalability of LLM-based servicesContribute to internal documentation, experimentation processes, and model evaluation frameworks
Key Requirements:
Master’s degree in Artificial Intelligence, Computer Science, or a related technical fieldStrong programming skills in Python, with experience in ML and data tooling (e.g., PyTorch, Pandas, NumPy, Scikit-learn)Preferred: 2+ years of professional software engineering experience, including scripting, data processing, or backend/ML pipelinesExperience with NLP techniques, LLMs, or machine learning fundamentalsStrong problem-solving ability and comfort working independently in a fast-moving environmentPreferred: Experience deploying applications or models on cloud platforms, preferably AWSBonus (not required): experience with real-time systems, WebSockets/streaming, RAG pipelines, vector databases, or ML evaluation frameworks, Genesys/Twilio
