5 of 5 Remote/Hybrid PyTorch Jobs in Cambridge

with video, audio, TV, or edge-device environments, especially where latency, cost, and hardware constraints matter. Familiarity with ML/DL frameworks such as PyTorch or TensorFlow. Research experience, paper implementation experience, or a habit of applying emerging GenAI techniques pragmatically to real problems. What's Roku's approach ...

solid system design, integration, data, CI/CD, observability, security, and cloud‐native practices. Strong Python skills and experience with frameworks such as PyTorch, TensorFlow, scikit-learn, LangChain, LangGraph, or similar. Experience with LLM and agentic patterns, including retrieval, orchestration, tool use, evaluation, guardrails, and governed production deployment. Solid understanding ...

functional teams. Excellent communications skills both written and verbal “Nice To Have” Skills and Experience: Experience with AI/ML frameworks such as TensorFlow, PyTorch, ONNX, or inference runtimes. System bring-up and JTAG debugging expertise Good background of system performance analysis Experience with RTL simulation tools and software development ...

demonstrate: Proven product management in development tools and software including CLIs, SDKs and APIs. Knowledge of machine learning frameworks, runtimes, infrastructure such as PyTorch, ONNX, ExecuTorch, Llama.cpp, vLLM and LiteRT. Understanding of model deployment to edge, embedded or heterogeneous computing, with an understanding of trade-offs between accuracy, performance ...

responsibilities include: Understanding emerging AI models, workloads and application use cases, and translating these into future software and hardware requirements. Working across ecosystems including PyTorch, ExecuTorch, LiteRT and ONNX , plus associated compilers, runtimes and kernel libraries. Evaluating emerging technologies and industry trends to understand their implications for Arm. Required Skills … Strong knowledge of modern AI models and workloads is also required. Candidates should understand the computational characteristics that determine performance on hardware. Familiarity with PyTorch, ExecuTorch, LiteRT, ONNX or ONNX Runtime is important. We also value: Understanding of how AI workloads move through graphs, compilers, runtimes and kernels to hardware. ...