Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of their trade-offs in terms of performance, cost, latency, and capabilities. Evaluate and deploy appropriate LLMs based on specific needs-balancing accuracy, latency, cost, and user experience.
Numbers & Facts
Location
San Diego, CA
Description
Our Client, an AV Manufacturing company, is looking for a Software Engineer for their San Diego, CA location.
Responsibilities:
Design and develop AI agents and autonomous systems capable of complex task execution and decision-making
Build conversational AI solutions including chatbots and voice-based customer service systems
Create AI-powered application integrations across platforms and services
Develop and optimize Retrieval-Augmented Generation (RAG) systems for enhanced AI application performance
Implement and optimize machine learning models using PyTorch
Evaluate and deploy appropriate LLMs based on specific needs-balancing accuracy, latency, cost, and user experience
Collaborate with cross-functional teams to translate business requirements into technical AI solutions
Architect and maintain production-grade AI solutions with focus on scalability, reliability, and performance
Requirements:
6+ years Proficiency in Python for AI/ML development
6+ years Experience with PyTorch (or willingness to learn for entry-level candidates)
Understanding of AI agents and their application to real-world problems
Hands-on experience or strong interest in building chatbots and/or voice-based conversational systems
Knowledge of RAG system components: vector databases, embeddings, retrieval strategies, and prompt engineering
Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of their trade-offs in terms of performance, cost, latency, and capabilities
Understanding of transformer neural network architecture and attention mechanisms
6+ years Experience integrating AI capabilities into applications or eagerness to learn application development
Proficiency in Kotlin programming
Full-stack development experience with both backend and frontend technologies
Cloud software development experience, especially microservices architecture and integration
Experience with REST APIs, gRPC, and/or Kafka for service communication and event-driven architectures
Knowledge of cloud platforms (AWS, GCP, Azure) for AI deployment
Familiarity with containerization and orchestration (Docker, Kubernetes)
Experience with AI frameworks like LangChain, LlamaIndex, AutoGen, or similar tools
Understanding of CI/CD pipelines and DevOps practices