Join Cognistack as a Founding AI Engineer to develop multimodal AI systems, focusing on computer vision and production-ready pipelines. 3-5 years of experience in applied AI/ML engineering required. Strong CS/ML background and experience with Python, PyTorch, and TensorFlow.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
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
- 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.
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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
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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: 📧 [email protected]
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