19 of 19 Permanent ONNX Jobs

bottlenecks, and optimizing them Good understanding of docker and containerization (Good to have) experience with Pytorch and Python3, and comfortable with C++ (Good to have) Understanding of Torch script, ONNX runtime, TensorRT (Good to have) Understanding of half-precision inference and int8 quantization What we offer Company equity % in an early-stage startup More ❯

C++ and/or Rust Experience with distributed data processing frameworks such as PySpark Experience with agentic learning models Experience using MLOps frameworks and components (e.g. DVC, Horovod, Spark, ONNX, Parquet) Familiarity with SQL and modern database technologies (e.g., MinIO, Yugabyte) Understanding of secure software development practices and/or experience working in classified environments Ability to build and manage More ❯

Newcastle. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯

RF principles (RSSI, phase, multipath, filtering, spectral analysis, DSP) * Experience with sensor fusion and time-series learning (LSTM, Transformers, probabilistic filters). * Familiarity with deployment on constrained hardware (Jetson, ONNX Runtime, TensorRT). *Education and Experience* * BS required, MS preferred in Computer Science, Electrical Engineering, or related field. * 2+ years of hands-on experience developing and deploying ML models for More ❯

deliver secure-by-design medical software. Maintain high standards of code quality through reviews, testing, and documentation. ✅ Must Haves Hands-on experience with AI inference acceleration (e.g. NVIDIA TensorRT, ONNX Runtime). Strong proficiency in Python for numerical and performance-focused computing. Expertise in hardware-accelerated video decoding/encoding using Python. Proficiency with NumPy, CuPy, SciPy , and related libraries. More ❯

deliver secure-by-design medical software. Maintain high standards of code quality through reviews, testing, and documentation. ✅ Must Haves Hands-on experience with AI inference acceleration (e.g. NVIDIA TensorRT, ONNX Runtime). Strong proficiency in Python for numerical and performance-focused computing. Expertise in hardware-accelerated video decoding/encoding using Python. Proficiency with NumPy, CuPy, SciPy , and related libraries. More ❯

deliver secure-by-design medical software. Maintain high standards of code quality through reviews, testing, and documentation. ✅ Must Haves Hands-on experience with AI inference acceleration (e.g. NVIDIA TensorRT, ONNX Runtime). Strong proficiency in Python for numerical and performance-focused computing. Expertise in hardware-accelerated video decoding/encoding using Python. Proficiency with NumPy, CuPy, SciPy , and related libraries. More ❯

performance. Requirements 5–7 years of experience in Computer Vision and Deep Learning with deployed production models. Strong proficiency in Python and PyTorch ; hands-on experience with OpenCV, TensorRT, ONNX, or Triton . Proven expertise in object detection/tracking models such as YOLO, Deep SORT, DINOv2 , or similar. Experience with real-time or low-latency processing , multi-threaded programming More ❯

functionality. Within these tasks, you will have the opportunity to develop skills with the following tools and platforms: Matlab and Simulink Python Deep Learning libraries (e.g. Pytorch, scikit-learn, ONNX) C/C++ Hardware development boards (e.g. NVIDIA Jetson products) Alongside involvement with departmental activities, you will be part of a wider cohort of summer placements and graduates on the More ❯

code and participate in reviews. Requirements: Advanced Python skills for numerical and performance-focused computing. Good experience with video processing/streaming software. Experience with AI inference acceleration (TensorRT, ONNX Runtime) and scientific libraries (NumPy, CuPy, SciPy). Expertise in hardware-accelerated video encoding/decoding. Strong documentation and communication skills; ability to own projects end-to-end. Nice to More ❯

projects end-to-end, from concept to production deployment. Skills & Experience Advanced Python skills with a focus on numerical computing and performance. Experience with AI inference acceleration (e.g., TensorRT, ONNX Runtime) and libraries like NumPy, CuPy, SciPy. Expertise in hardware-accelerated video encoding/decoding using Python. Strong communication skills and ability to write maintainable, well-documented code. Self-starter More ❯

into Back End systems to enhance product functionality. AI Model Integration: Embed pre-trained Generative AI models and Agentic frameworks (A2A, MCP) into scalable applications. Optimize inference pipelines using ONNX , TensorRT , or similar tools. Ensure smooth communication between Front End , Back End , and AI endpoints . Cloud & DevOps: Deploy and manage applications on Microsoft Azure using AKS (Azure Kubernetes Service … HTML5 , CSS3 , Tailwind CSS , Material-UI Back End: Python (Flask, FastAPI, Django) , RESTful/GraphQL APIs Experience with SQL and NoSQL databases (PostgreSQL, MongoDB, etc.) AI Integration: Familiarity with ONNX , TensorFlow Serving , A2A , MCP , and Generative AI models Cloud & DevOps: Azure , Databricks , Terraform , Docker , Kubernetes CI/CD pipelines using Azure DevOps , GitHub Actions , or Jenkins Version Control: Git , GitHub More ❯

the back end. - Implement secure authentication and data processing pipelines. AI Model Integration: - Embed pre-trained Generative AI models and Agentic frameworks. - Optimize model inference pipelines using tools like ONNX and TensorRT. - Ensure efficient communication between front-end, back-end, and AI endpoints. Cloud and DevOps: - Deploy applications on Azure using services like AKS and Azure Functions. - Utilize Databricks for …/TypeScript, HTML5, CSS3, Tailwind CSS or Material-UI. - Back-End: Python (Flask, FastAPI, Django), RESTful/GraphQL APIs, SQL/NoSQL databases. - AI Integration: Familiarity with frameworks like ONNX and TensorFlow Serving. A2A & MCP - Cloud Platforms: Azure, Databricks. - DevOps: CI/CD pipelines, Terraform, Docker, Kubernetes. - Version Control: Git (GitHub). Good-to-Have Skills: - Node.js, real-time back More ❯

Head of AI Logistics Company (Up to £180,000 per annum + Equity) London (3 days per week in office) La Fosse has partnered with an ambitious AI-driven logistics company that’s redefining how supply chains operate. They are More ❯

Head of AI Logistics Company (Up to £180,000 per annum + Equity) London (3 days per week in office) La Fosse has partnered with an ambitious AI-driven logistics company that’s redefining how supply chains operate. They are More ❯

Head of AI Logistics Company (Up to £180,000 per annum + Equity) London (3 days per week in office) La Fosse has partnered with an ambitious AI-driven logistics company that’s redefining how supply chains operate. They are More ❯

Head of AI Logistics Company (Up to £180,000 per annum + Equity) London (3 days per week in office) La Fosse has partnered with an ambitious AI-driven logistics company that’s redefining how supply chains operate. They are More ❯

Head of AI Logistics Company (Up to £180,000 per annum + Equity) London (3 days per week in office) La Fosse has partnered with an ambitious AI-driven logistics company that’s redefining how supply chains operate. They are More ❯

using modern frameworks and libraries. Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance … Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version … in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version More ❯