CUDA Jobs

The immediate goal is to bring fully-functioning validator and miner nodes for both Gonka AI and Bittensor online, running on rented H100 GPU servers. I already have the hardware allocated and wallets ready; what I need is an engineer who can take the nodes from zero to profitable operation and then keep them humming. Key tasks • Provision and secure each H100 instance, configure networking, firewalls, SSH keys and wallets • Containerise the stacks with Docker (Kubernetes or Podman are possible later, but Docker is fine for the first iteration) • Tune CUDA-level settings so every GPU cycle counts and rewards are maximised • Build simple Bash or Python scripts that monitor logs, restart on failure and push basic alerts • Produce step-by-step documentation...

I’m putting together a series of college-level workshops and need an expert who can both design and deliver engaging, lab-style sessions on AI, NLP, and machine learning. The audience will be under-grad and post-grad students who already code in Python but have limited exposure to real-world AI pipelines. Scope The program should span three core tracks—an approachable “Introduction to AI & ML,” a set of “Hands-on NLP Projects” that let students build something tangible, and a closing block on “Advanced Machine Learning Techniques” that shows them what’s possible beyond the basics. Because the colleges have explicitly asked for hands-on labs rather than slide-only lectures, your material needs to revolve around live coding, intera...

I want to build a Windows-only application that watches the live screen, detects people—including stylised in-game characters—in real time, and immediately drives a game controller so the crosshair locks onto and tracks that target as it moves. The workflow I picture is straightforward: the program captures frames, an AI model spots the person, and a virtual stick signal (XInput, vJoy or a comparable driver) nudges the aim every frame so it stays centred. Smoothness and speed are critical. On a 1080p feed I’m aiming for roughly 60 fps with no more than 40–50 ms end-to-end latency, so techniques such as YOLOv8, TensorRT or a lightweight custom network combined with OpenCV screen capture should fit. You’re free to choose Python, C++, or another language as long...

I need targeted support integrating and extending three NASA-developed codes—NEQAIR, SIDPAC and POST—inside my current analysis workflow. The work centres on writing and refining custom scripts in Fortran, C++, Python or Matlab that automate set-ups, run batches offline, and export results in a research-ready format. Scope • NEQAIR: build or modify driver routines that sweep radiative parameters for several shock-layer cases I will provide. • SIDPAC: create data-reduction and parameter-estimation scripts that plug directly into flight-test MATLAB sessions. • POST: draft trajectory set-up files and helper utilities so I can reproduce reference missions without the GUI. Key technical needs – Proven, hands-on experience with at least two of these NAS...

I have a kaggle dataset containing colored images and thermal image .. do feature extraction and then combine them and the do feature extraction on it