Harry Crick

Job Title: AI Researcher Location: Bay Area (Hybrid) Compensation: $250K–$290K + Equity We’re hiring on behalf of a fast-growing, well-funded Bay Area startup redefining video creation using generative AI. Their platform enables video-to-video generation — combining diffusion models, Gaussian splatting, and human-centric 3D rendering. In this role, you’ll:Research and deploy models for video generation, in-painting & 3D simulationWork on human-centric modeling (pose, movement, reenactment)Build on top of diffusion models, transformers, and neural rendering methodsCollaborate with a multidisciplinary team of researchers, engineers & artistsIdeal candidates have:A PhD (or equivalent) in AI, CV, or graphicsPublications in top venues (CVPR, NeurIPS, ICCV, SIGGRAPH, etc.)Strong experience with generative models or visual computingApply now to work on bleeding-edge visual AI with real-world impact.

Job Title: MLOps EngineerWork Arrangement: RemoteLocation: Toronto, CanadaSalary: Up-to $125,000 CADMLOps Engineer – Real-Time AI SystemsWe're looking for an experienced MLOps Engineer to help deploy and scale cutting-edge ML models for real-time video and audio applications. You'll work alongside data scientists and engineers to build fast, reliable, and automated ML infrastructure.Key ResponsibilitiesBuild and manage ML pipelines for training, validation, and inference.Automate deployment of deep learning and generative AI models.Ensure model versioning, rollback, and reproducibility.Deploy models on AWS, GCP, or Azure using Docker and Kubernetes.Optimize real-time inference using TensorRT, ONNX Runtime, or PyTorch.Use GPUs, distributed systems, and parallel computing for performance.Create CI/CD workflows (GitHub Actions, Jenkins, ArgoCD) for ML.Automate model retraining, validation, and monitoring.Address data drift, latency, and compliance concerns.What You Bring3+ years in MLOps, DevOps, or model deployment roles.Strong Python and experience with ML frameworks (PyTorch, TensorFlow, ONNX).Proficiency with cloud platforms, Docker, and Kubernetes.Experience with ML tools like MLflow, Airflow, Kubeflow, or Argo.Knowledge of GPU acceleration (CUDA, TensorRT, DeepStream).Understanding of scalable, low-latency ML infrastructure.Nice to HaveExperience with Ray, Spark, or edge AI tools (Triton, TFLite, CoreML).Basic networking knowledge or CUDA programming skills.

Job Title: AI ResearcherWork Arrangement: HybridLocation: San JoseWe are seeking a talented Computer Vision AI Researcher with expertise in stable diffusion, diffusion models, GANs, NeRFs, and text-to-image/video synthesis.Key Responsibilities:Conduct pioneering research in computer vision, focusing on diffusion models and text-to-Image/videoDevelop advanced GAN architectures tailored for specific computer vision applications.Investigate NeRFs and related techniques to enhance 3D scene understanding.Drive advancements in text-to-image and text-to-video synthesis using deep learning methods.Collaborate closely with cross-functional teams to productise researchQualifications:Strong research background in stable diffusion, GANs, NeRFs, and text-to-image/video synthesis, evidenced by publications in top-tier conferences or journals.Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).Experience with large-scale data processing and model training.

Computer Vision Engineer – Hybrid Los Angeles – Up to $220k + Bonus + Equity Startup of 10+ engineers building next-stage real-time vision and sensing systems for defense and autonomy. Profitable and customer funded with no outside investment. Their platforms span digital terrain mapping, classical computer vision, and high performance signal processing, with hardware already deployed in the field. What You’ll Be DoingDesigning and implementing low-latency vision pipelines in C++ for mission-critical defense applications (e.g., region-of-interest tracking, camera calibration, sensor fusion).Collaborating closely with hardware teams to integrate cameras, IMUs, and other sensors on embedded platforms—pushing algorithms from prototype to production.Conducting field-testing (flight tests, desert range tuning) to validate and optimize real-world performance.Working on digital terrain modeling, object-tracking algorithms (drone-to-drone intercept, remote weapons platforms), and AR/display research.Writing reusable, well-documented code that ensures reliability under harsh conditions and tight real-time constraints.Must-Haves3+ years of professional experience developing C++ systems (preferably on Linux).Strong background in classical computer vision or signal processing (Kalman filters, ROI tracking, camera calibration, etc.).Comfortable working hands-on with sensors, cameras, and embedded hardware.Interest in field testing and tuning algorithms in live environments.U.S. Citizen or Green Card holder (required for defense-related work).Nice-to-HavesCUDA/OpenCL experience or other GPU-accelerated development.Prior work on SLAM or visual-inertial odometry for airborne or ground-robot platforms.Experience architecting software for long-range tracking (drones, aircraft, missiles).Familiarity with ROS, RTOS, or other robotics middleware.