Lendbuzz is hiring a Software Engineer

Lendbuzz is hiring a Software Engineer focused on Large Language Model (LLM) applications to join our Machine Learning team. You will help design, build, and optimize next-generation conversational agent technologies, collaborating closely with ML researchers and product teams.

What You'll Do

• Engineer software for LLM-powered conversational agents, with an emphasis on practical implementation, reliability, and user experience.
• Evaluate, fine-tune, and deploy LLM-based models and pipelines using REST APIs and internal microservices.
• Implement prompt engineering, retrieval-augmented generation (RAG), tool-use pipelines, and conversation orchestration logic.
• Investigate and integrate emerging technologies, particularly in real-time voice, streaming, and multi-modal interaction.
• Analyze model outputs, user interactions, and system performance to drive iterative improvements.
• Build and maintain high-quality datasets, including data cleaning, preprocessing, labeling workflows, and benchmarking for NLP tasks.
• Own data quality, ensuring accuracy, reproducibility, and reliability across the data lifecycle.
• Collaborate with ML, backend, and product teams on deployment best practices, monitoring, and scalability of LLM-based services.
• Contribute to internal documentation, experimentation processes, and model evaluation frameworks.

What We're Looking For

• A Master’s degree in Artificial Intelligence, Computer Science, or a related technical field.
• Strong programming skills in Python, with experience in ML and data tooling (e.g., PyTorch, Pandas, NumPy, Scikit-learn).
• Experience with NLP techniques, LLMs, or machine learning fundamentals.
• Strong problem-solving ability and comfort working independently in a fast-moving environment.

Nice to Have

• 2+ years of professional software engineering experience, including scripting, data processing, or backend/ML pipelines.
• Experience deploying applications or models on cloud platforms, preferably AWS.
• Experience with real-time systems, WebSockets/streaming, RAG pipelines, vector databases, ML evaluation frameworks, or platforms like Genesys/Twilio.

Technical Stack

• Python, PyTorch, Pandas, NumPy, Scikit-learn
• AWS, REST APIs, microservices
• RAG, vector databases
• Genesys/Twilio

Team & Environment

You will be part of the Machine Learning team and report to an ML Research Scientist.

Work Mode

This is a hybrid role based in Boston, MA.

Lendbuzz is an equal opportunity employer where diversity is a competitive advantage, compassion is a strength, and honesty and transparency are non-negotiable.