15 of 15 ONNX Jobs

Waterfall, Lean. Programming Language: C++, Python, Shell, SQL, R. IDE Tools: PyCharm, RStudio, Visual Studio Code, Jupyter Notebook, Google Collab, Navicat. ML Frameworks: Transformers, Scikit-Learn, Keras, TensorFlow, PyTorch, ONNX, NLTK, OpenAI, langchain, llama-index,kore.ai. DL Architectures: LLM, ANN, CNN, R-CNN, RNN, GRU, LSTM, Transformers, Attention Mechanism, Tokenisers. BERT, T5, Sentence Transformers, Foundational models. Packages: Pandas, NumPy, Spark More ❯

and ability to work in a hybrid, collaborative environment. Nice to Have Experience with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

and ability to work in a hybrid, collaborative environment. Nice to Have Experience with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

and ability to work in a hybrid, collaborative environment. Nice to Have Experience with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

and ability to work in a hybrid, collaborative environment. Nice to Have Experience with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

and ability to work in a hybrid, collaborative environment. Nice to Have Experience with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management Industry experience with machine learning teams Working knowledge of common ML frameworks such as PyTorch, ONNX, DeepSpeed etc. Prior experience with cloud-native technologies like Kubernetes, Argo Workflows, Buildpacks, etc. Experience with cloud providers such as AWS, GCP or Azure A track record of collaboration with More ❯

experience communicating methodological choices and model results. • Demonstrated experience with verification and validation test benches. • Demonstrated experience with Explainable AI (XAI) techniques. • Demonstrated experience with Open Neural Net Exchange (ONNX). More ❯

Demonstrated academic or professional experience communicating methodological choices and model results. • Demonstrated experience with verification and validation test benches. • Demonstrated experience with Explainable AI (XAI) techniques. • Demonstrated experience with ONNX (Open Neural Net Exchange) Salary Range: $150,000-$200,000 All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national More ❯

trends in ML models, software stacks, and hardware architectures. PREFERRED EXPERIENCE: Proficiency in Python and C/C++ programming. Deep understanding of AI/ML algorithms, frameworks (e.g., PyTorch, ONNX), and model representations. Experience in analytical modeling of ML operators regarding compute and data movement. Background in optimization libraries and solvers like PuLP, CBC, Gurobi is advantageous. Effective communication and More ❯

a related discipline. Strong expertise in PyTorch and C++ programming. Experience with ML workload analysis, compiler development, and quantization techniques. Familiarity with deep learning frameworks such as TensorFlow or ONNX is a plus. Proven track record of solving complex performance and efficiency challenges in hardware-aware ML solutions. Ability to work collaboratively with strategic customers and deliver impactful results. Excellent More ❯

prototype, and implement compiler and system-level optimizations Qualifications Strong background in PyTorch and C++ programming Experience in ML compiler development, quantization, and workload analysis Familiarity with TensorFlow or ONNX a plus Solid understanding of hardware-aware ML solutions and performance optimization Excellent problem-solving, collaboration, and communication skills Preferred Qualifications Experience deploying ML models on NPUs, GPUs, or TPUs More ❯

Version Control Optimization Strategic Thinking & Problem Solving Desirable: Excellent cross-cultural communication and leadership skills for distributed teams Ability to manage up effectively with senior leadership Experience with ML.NET, ONNX Runtime, Semantic Kernel, and/or RavenDB AI capabilities. Exposure to managing geographically dispersed teams across multiple time zones Prior success in leading organizational transformation initiatives Key duties: Build a More ❯

define, prototype, and ship new AI-powered features including text-to-speech, image generation, and enhanced tool calling capabilities Implement and optimize model serving infrastructure using frameworks like vLLM, ONNX Runtime, and Nvidia Triton to achieve production-scale performance requirements Collaborate with DevOps teams on MLOps infrastructure including model monitoring, load testing, caching optimization, and automated CI/CD pipelines … engineering background with production experience Extensive experience with PyTorch or other modern ML frameworks Experience training custom models from scratch Experience with model optimization and inference frameworks (e.g., vLLM, ONNX Runtime, Nvidia Triton) Familiarity with MLOps practices & Kubernetes and ability to collaborate with DevOps teams on model monitoring, load testing, and CI/CD pipelines Experience shipping ML-powered features More ❯

the deployment methods for GPU-accelerated serving frameworks in the market, with reference implementations and best-practice recommendations for large-scale serving solutions (eg, NVIDIA Triton Inference Server, TensorRT, ONNX Runtime). Develop repeatable and automated configuration templates for GPU resources. Implement active GPU monitoring, including review and analysis of all relevant metrics (utilization, memory bandwidth, power, temperature, etc.), and … NVIDIA Certified (Preferred). Required Skills Direct experience with GPU services, including resource provisioning, scaling, and optimization. Demonstrable expertise in GPU-accelerated software development (CUDA, OpenCL, TensorRT, PyTorch, TensorFlow, ONNX, etc.). Strong background in performance benchmarking, profiling (Nsight, nvprof, or similar tools), and workload tuning. Experience with Infrastructure as Code (Terraform, HELM Charts, or equivalent) for automated cloud resource More ❯