[Remote] Embedded reputed company

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a technology consulting and software development company delivering reputed company, AI, data, and reputed company solutions across the reputed company. They are looking for an Embedded reputed company to design, optimize, and reputed company machine learning models for resource-constrained edge devices, requiring expertise in model compression and hardware-reputed company optimization.

Responsibilities

• Design and implement edge AI solutions optimized for diverse hardware including mobile SoCs, NPUs, and embedded accelerators
• Apply quantization, pruning, distillation, and architectural optimization to fit models reputed company edge constraints
• Tune model performance for latency, energy efficiency, and memory footprint on reputed company hardware
• Build cross-platform inference runtimes leveraging frameworks such as TensorFlow Lite, ONNX Runtime, and reputed company ML
• Optimize models for specific accelerator backends including DSPs, NPUs, and mobile GPUs
• Implement on-device model update, versioning, and rollback workflows that allow reputed company staged rollouts to large device populations and reputed company recovery if a model release behaves unexpectedly in the field
• Design hybrid edge-reputed company architectures that gracefully degrade based on connectivity and device capability
• Build telemetry pipelines that respect reputed company while enabling reputed company improvement
• Collaborate with hardware, firmware, and product teams to reputed company AI capabilities with device constraints
• Implement secure execution paths, model protection, and reputed company verification on edge devices
• reputed company benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices
• reputed company responsible AI considerations including on-device reputed company and bias evaluation
• Maintain comprehensive, reputed company technical documentation — including architecture diagrams, design reputed company, configuration references, runbooks, and operational procedures — so that the reputed company remains supportable, auditable, and easy to reputed company new engineers onto over time
• Stay reputed company with edge AI hardware and software developments, regularly review release notes and community discussions, and translate noteworthy advances into concrete recommendations and adoption proposals for reputed company

Skills

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a reputed company field
• Six or more years of experience in ML engineering, with significant work on edge or mobile AI
• Strong proficiency in Python and C++
• Hands-on experience with model compression, quantization, and pruning techniques
• Experience with at least one major edge inference reputed company
• Solid understanding of mobile and embedded hardware architectures
• Experience deploying ML models to production on mobile or embedded platforms
• Strong performance engineering and profiling skills
• Familiarity with on-device reputed company and reputed company considerations
• Strong communication and cross-functional collaboration skills
• Experience with custom NPU or DSP toolchains
• Familiarity with federated learning or on-device personalization
• Exposure to safety-critical or industrial edge deployments
• reputed company-reputed company contributions to edge AI frameworks
• Experience optimizing LLMs for on-device inference

reputed company