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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Founding Machine Learning Engineer - **Company:** David Joseph & Company - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $180,000.0 - $230,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Customer Data Management, Python (Programming Language), Machine Learning, Language Modeling, Open Source Technology, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Discretization, Information Technology, ONNX (Open Neural Network Exchange) Format, HuggingFace, Ray Serve, TensorRT, VLLM, Wearables, Docker - **Published:** October 2, 2026 - **Apply:** https://www.thejobnetwork.com/job/00336553-8629-4627-903c-9c4411c7f689/founding-machine-learning-engineer ## About the Role * Up to 3 years of hands-on experience building and deploying multimodal or vision-language AI systems in Python and PyTorch * A track record of shipping vision-language systems that real users rely on in production, where you owned both the model and the orchestration layer, rather than demos or research prototypes * Practical depth in applied model work such as fine-tuning (SFT, RLHF), evaluation design, and orchestrating models in production, including visual reasoning and detection or segmentation where needed * Experience building agents that plan across multiple steps and call tools, along with the evaluation harnesses and data loops that keep them improving * Experience as a founder or very early engineer at a startup, or at a fast-paced, high-intensity engineering organization * A bachelor's or master's degree in computer science, machine learning, or engineering from a strong program, or equivalent experience shown through production AI work * Real enthusiasm for computer vision, wearables, and industrial AI, visible in your projects, side work, or career path * Ability to work on-site in San Francisco five days a week; openness to shared team housing is a plus * Existing US work authorization; our client can support visa transfers (for example OPT or H-1B transfer) but cannot sponsor new visas Nice to Haves * Experience shipping AI for AR or wearable devices, or computer vision for autonomous driving * A master's degree that included vision or multimodal research, such as a thesis or published work * Experience deploying open-weight models at the edge or on-premise on constrained hardware using tools like vLLM, Triton, TensorRT, or quantization techniques ## Description Our client is hiring a founding machine learning engineer to own the AI core of their product from day one. You will build and ship multimodal systems that run on real hardware in the field, working directly with the founding team in a fast-moving, in-person environment. This role suits a hands-on builder who has put vision-language or multimodal systems in front of real users. What you'll be doing * Building a production pipeline of multi-step, tool-using visual reasoning agents that run on smart glasses against real industrial workflows such as inspections and standard operating procedures * Creating real-time voice and video AI interfaces for the glasses, including conversational and proactive alert modes tailored to different users * Owning evaluation and the data flywheel: eval harnesses, capturing failure modes, and turning customer data into fine-tuning loops that improve model quality release over release * Delivering edge inference and model orchestration that adapts gracefully to changing connectivity and latency constraints in the field * Fine-tuning and optimizing open-source multimodal models (SFT, RLHF, quantization) for on-premise enterprise deployments Tech stack: Python, PyTorch, vLLM, Triton, Ray Serve, ONNX, TensorRT, Hugging Face Transformers, LangChain, RAG, RLHF, SFT, quantization (GPTQ, AWQ), edge AI, multimodal LLMs, vision-language models, Docker ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [ I Gave a Video Editor More Autonomy Than a Trading Bot. On Purpose.](https://www.wearedevelopers.com/magazine/773-i-gave-a-video-editor-more-autonomy-than-a-trading-bot-on-purpose)