Software Engineer (Machine Learning - LLMs)

Key Responsibilities:

• Software engineering 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

Key Requirements:

• 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)
• Preferred: 2+ years of professional software engineering experience, including scripting, data processing, or backend/ML pipelines
• Experience with NLP techniques, LLMs, or machine learning fundamentals
• Strong problem-solving ability and comfort working independently in a fast-moving environment
• Preferred: Experience deploying applications or models on cloud platforms, preferably AWS
• Bonus (not required): experience with real-time systems, WebSockets/streaming, RAG pipelines, vector databases, or ML evaluation frameworks, Genesys/Twilio