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.
