Location
Job description
Job Title: Founding AI Engineer (Multimodal AI / Computer Vision)Company: Cognistack Location: San Francisco, CA (On-site, 5 days per week) Employment Type: Full-time Salary: $180,000 - $240,000/year Experience Level: Mid-level (3-5 years) Education Level: Bachelor’s (Master’s preferred with vision/multimodal research component)About the Role We are seeking a Founding AI Engineer to join our team in San Francisco. This role focuses on applied AI/ML engineering, specifically within computer vision and multimodal systems. The ideal candidate has shipped agentic multimodal systems to real users and is comfortable building production Vision-Language Model (VLM) pipelines with real hardware constraints. Key Responsibilities
Requirements
Technical Stack
Additional Information
How to Apply If you have the required skills and experience, please send your resume with details to: 📧 skumar@cognistack.co
- Build and ship production agentic-VLM pipelines running on industrial smart glasses, including multi-step, tool-using visual-reasoning loops against real customer workflows (SOPs, inspection, field service).
- Own model orchestration and runtime optimization for edge inference, balancing model quality against latency with graceful fallback across connectivity conditions.
- Design and build the evaluation harness and data flywheel from scratch, including failure-mode capture, customer-data fine-tune loops, and measurable model quality improvements.
- Ship real-time voice-video AI interfaces adapted to different end-user profiles (video-heavy, conversational speech, and proactive alerts).
- Build RAG pipelines for the efficient creation and querying of enterprise knowledge bases from field operator data.
- Drive multimodal model training for on-premise deployments, including open-source model SFT, RL post-training, and quantization.
Requirements
- Experience: 3-5 years of experience in applied AI/ML engineering, ideally in computer vision or multimodal systems.
- Production Track Record: Demonstrated experience shipping multimodal and computer vision systems in the VLM era (production, not demos or pure research). Must have owned the model layer end-to-end.
- Background: Experience at a startup or AI team building production AI products is preferred. Big-company tenure (e.g., Meta Reality Labs, Snap, Apple Vision, Google) is a bonus only if on a directly relevant team (AR/smart-glasses, real-time video/streaming, on-device/edge ML) or paired with a builder signal (founder/early-startup/side projects/OSS). Long single big-tech tenure with no builder signal and no relevant-team work is not a fit.
- Domain Experience: Production AR/wearable AI experience or autonomous driving Computer Vision is preferred. Industrial domain exposure (data centers, energy grid, aerospace, manufacturing) is a plus.
- Technical Skills:Applied VLM/Multimodal Engineering: Shipping, hardening, and applied fine-tuning of vision-language/video-language models.
- Applied Agentic AI/Model Orchestration.
- Rigorous evaluation disciplines (ground-truth, trajectory/tool-call accuracy, regression).
- On-prem/self-hosted model deployment and optimization.
- In-context grounding/RAG against knowledge bases.
- Education: Strong CS/ML/Engineering background or demonstrated equivalent shipping record. Master’s with a vision or multimodal research component is preferred.
Technical Stack
- Python, PyTorch, TensorFlow
- vLLM, Triton, Ray Serve, ONNX, TensorRT
- Hugging Face Transformers
- LangChain, RAG
- RLHF, SFT, Quantization (GPTQ, AWQ)
- Edge AI, Multimodal LLMs, Vision-Language Models
- Docker
Additional Information
- Visa Sponsorship: H-1B transfers and TN visas are supported. No new H-1B sponsorship.
- Location Requirement: Candidates must currently reside in the USA or Canada.
- Work Style: Ideally willing to join a hacker house (live on site). At minimum, must be willing to work on-site 5 days per week in San Francisco.
- Referral Bonus: $5,000 for successful placements.
How to Apply If you have the required skills and experience, please send your resume with details to: 📧 skumar@cognistack.co