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Develops advanced AI models for clinical simulations and drug development, focusing on transformers, foundation models, and biomedical data analysis to predict patient outcomes and optimize trial design.
Build and maintain open-source machine-learning tools for neuroscience research, using Python, PyTorch/TensorFlow, and UI frameworks to create reusable, well-documented software for the scientific community.
Lead end-to-end design and delivery of large-scale AI systems for federal programs, building Python-based LLM and generative AI solutions with cloud-native architectures and MLOps pipelines.
Freelance ML/Python developer builds and deploys computer-vision models (YOLO, DETR, ResNet) using PyTorch, optimizes inference pipelines on Nvidia GPUs, and integrates them via APIs on AWS.
Build and deploy ML models for vehicle telemetry and diagnostics, owning end-to-end pipelines from data to production to reduce fleet downtime and maintenance costs.
AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched…
Build and evaluate frontier AI coding agents by solving complex ML engineering tasks, reviewing model-generated code, and identifying bugs or performance issues in production-ready systems.
Build and maintain the distributed training and inference infrastructure that powers a startup’s AI research, using PyTorch, vLLM/SGLang, and GPU schedulers to scale physics-discovery models.
Build and deploy AI/ML models in Python to extract insights from large datasets and advise stakeholders on data-driven decisions.
Freelance AI/ML engineers advise clients or join emagine’s teams on projects using Python/R, TensorFlow/PyTorch, and cloud platforms like AWS/Azure to build, deploy, and optimize models for enterprise clients.
Build and deploy generative AI and LLM solutions, designing NLP pipelines and scalable ML systems for clients using Python, TensorFlow/PyTorch, and cloud MLOps.
Build and deploy ML models for gaming and ad platforms: recommendations, uplift, visual embeddings, and marketing predictions using Python, TensorFlow/PyTorch, and MLflow.
Build and scale distributed systems that power low-latency AI inference for a physical-world LLM platform, optimizing GPU clusters and cloud infrastructure.
Build and improve deep-learning models to detect audio deepfakes, using PyTorch and modern audio feature pipelines like spectrograms and wavelets.
Build ML models to personalize promotions and predict customer churn for a large Russian grocery retailer, using Python, PySpark, and PyTorch.
About David AI David AI is the first audio data research company. We bring an R&D approach to data–developing datasets with the same rigor AI labs bring to models. Our mission is to bring AI into the real world,…
About Us: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and…
Develop and optimize GPU-based rendering and machine learning components for real-time visual applications, integrating ML models into graphics pipelines using DX12/Vulkan and ONNX/TensorRT, while profiling and tuning for performance.
Builds automated data pipelines for autonomous-vehicle perception models, including mining, preprocessing, auto-labeling, and ground-truth generation on NVIDIA’s DRIVE platform using Python, C++, CUDA, and deep-learning frameworks.
Build and deploy AI/ML models, including generative AI and LLMs, using Python and cloud platforms like Azure OpenAI and Vertex AI.
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