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Join our Field Operations Team testing and validating automotive software directly on real vehicles; trucks, cars, and off-road. Use scan tools to test new releases, report bugs, help reproduce issues, and work alongside engineers to improve our products, always following safety procedures. Strong interest in vehicles required; diagnostic tool experience is a plus, along with attention to detail and comfort working outdoors.

Support three engineering leads with day-to-day administrative needs; agendas, task tracking in Jira, data entry, and inventory/shipping coordination across vendors and locations plus personal and lifestyle support for our CEO during his time in Mexico City, including travel, household services, reservations, and errands. Fluent in English and Spanish, highly discreet, comfortable across Google Suite, Jira, ClickUp, Slack, and AI tools, and able to operate with minimal supervision.

Design, train, optimize, and deploy LLMs in on-prem and offline environments from supervised fine-tuning (LoRA/Q-LoRA) to full RAG pipeline design and MCP (Model Context Protocol) integrations that let models interact securely with internal tools and data. Strong Python/ML background (PyTorch or TensorFlow, Hugging Face Transformers), experience with vector stores (FAISS, Chroma, Weaviate, pgvector), quantization (GGUF/GPTQ/AWQ), and deployment via vLLM, TGI, or Ollama in air-gapped, restricted-network environments required.

Design, train, optimize, and deploy LLMs in on-prem and offline environments from supervised fine-tuning (LoRA/Q-LoRA) to full RAG pipeline design and MCP (Model Context Protocol) integrations that let models interact securely with internal tools and data. Strong Python/ML background (PyTorch or TensorFlow, Hugging Face Transformers), experience with vector stores (FAISS, Chroma, Weaviate, pgvector), quantization (GGUF/GPTQ/AWQ), and deployment via vLLM, TGI, or Ollama in air-gapped, restricted-network environments required.

Build end-to-end LLM pipelines for on-prem and offline environments, from data preprocessing and fine-tuning through production RAG design and MCP-based tool integrations. This role puts extra weight on retrieval quality: hands-on experience with advanced RAG techniques like HyDE and multi-hop retrieval is a core requirement here, not just a nice-to-have. Strong Python/ML background (PyTorch or TensorFlow, Hugging Face Transformers), quantization (GGUF/GPTQ/AWQ), and GPU/CUDA optimization also required.

Be the face of Salvo Software in the field, network at industry events, prospect and start conversations with businesses ready for a technology partner, lead discovery calls, and collaborate with our technical team on proposals through close. Proven sales experience, hands-on HubSpot experience, strong communication skills, and a self-starter mentality required, with comfort in a performance-driven comp structure.