Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4336033086&distance=25.0&f_AL=true&f_TPR=r10000&f_WT=2&geoId=103644278&keywords=machine%20learning&origin=JOBS_HOME_KEYWORD_HISTORY Job Description: Senior AI Engineer  San Francisco Bay Area · Reposted 31 minutes ago · Over 100 applicants Promoted by hirer · Actively reviewing applicants Remote Matches your job preferences, workplace type is Remote. Full-time Easy Apply Save Save Senior AI Engineer  at Harrison Clarke Senior AI Engineer Harrison Clarke · San Francisco Bay Area (Remote) Easy Apply Save Save Senior AI Engineer  at Harrison Clarke Show more options Your profile is missing required qualifications Show match details Help me update my profile BETA Is this information helpful? Get personalized tips to stand out to hirers Practice mock interviews personalized to every role and get custom feedback Try Premium for PKR0 Meet the hiring team Bradley Green 3rd Search & Venture with Harrison Clarke | Partnering with Venture Capital firms across the United States Job poster Message About the job Senior AI Engineer - Video Search (Applied Research & Product) Remote - United States About the Company We’re partnering with a U.S-based applied AI company building next-generation real-time video understanding systems deployed at scale across enterprise, government, and public environments. The platform combines cutting-edge multimodal AI, vector search, and high-performance inference pipelines to make visual data searchable, interpretable, and actionable in real time. This is a chance to join a well-funded, mission-driven organization with over tens of thousands of active camera streams and a rapidly growing R&D team pushing the boundaries of multimodal retrieval and AI systems design. The Role We’re looking for a Senior AI Engineer to lead the applied research and productionization of our video search and retrieval stack - connecting natural-language queries to high-dimensional video representations with real-time performance. You’ll work at the intersection of deep learning research, scalable systems, and GPU-optimized inference, owning models and pipelines end-to-end from training through deployment. What You’ll Do Design and build natural-language-to-video retrieval systems using state-of-the-art architectures (e.g., V-JEPA, CLIP, SigLIP, Video-LLMs, ViViT, TimeSformer). Develop temporal localization and video summarization capabilities with fine-grained moment-level embeddings. Stand up vector search infrastructure (FAISS, Milvus, pgvector, Pinecone) with optimized sharding, caching, and hybrid retrieval strategies. Optimize GPU inference and serving pipelines using ONNX Runtime, TensorRT, or ROCm for low-latency performance. Drive multi-GPU training and distributed serving (FSDP, ZeRO, DDP, NCCL/RCCL) with strong understanding of parallelization and quantization techniques. Collaborate with MLOps, backend, and product teams to deliver production-ready AI features at scale. Define and track key retrieval and relevance metrics (R@K, mAP, nDCG) and run live A/B evaluations. Mentor junior engineers, document design decisions, and drive innovation through rigorous experimentation. What We’re Looking For 6-10+ years of experience in machine learning or applied AI, with 4+ years focused on video understanding, multimodal retrieval, or transformer-based models. Proficiency in PyTorch and deep learning frameworks; experience with video backbones, contrastive training, and representation learning. Strong understanding of vector databases, ANN search (HNSW, IVF), and embedding pipelines. Demonstrated ability to ship high-performance AI systems with GPU optimization, ONNX/TensorRT, or ROCm pipelines. Experience with distributed training, CI/CD for ML, and scalable data pipelines (MLflow, W&B, K8s, Docker). Excellent communication skills and a collaborative, low-ego approach to problem solving. Nice-to-Haves Experience with temporal detection, video tracking, or re-ID. Exposure to Video-RAG or structured retrieval (metadata + knowledge graph). Background in real-time or edge inference systems. Interest in privacy-preserving or regulated AI systems. Compensation & Logistics Compensation: Competitive base salary + bonus + equity Location: Fully remote (U.S. based) Why Join Build real-world AI that operates at scale and latency levels few companies ever reach. Collaborate with world-class engineers and researchers in a fast-paced, mission-oriented environment. Work on deep technical challenges - multimodal search, retrieval, inference optimization - with real-world outcomes.