[Remote] Edge AI Engineer
Note: The job is a remote job and is open to candidates in USA. Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. They are seeking a skilled Edge AI Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices. The role requires deep expertise in model compression, quantization, and hardware-aware optimization, along with strong systems engineering skills to ship reliable AI capabilities outside the data center.
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 within edge constraints
- Tune model performance for latency, energy efficiency, and memory footprint on target hardware
- Build cross-platform inference runtimes leveraging frameworks such as TensorFlow Lite, ONNX Runtime, and Core ML
- Optimize models for specific accelerator backends including DSPs, NPUs, and mobile GPUs
- Implement on-device model update, versioning, and rollback workflows that allow safe staged rollouts to large device populations and rapid recovery if a model release behaves unexpectedly in the field
- Design hybrid edge-cloud architectures that gracefully degrade based on connectivity and device capability
- Build telemetry pipelines that respect privacy while enabling continuous improvement
- Collaborate with hardware, firmware, and product teams to align AI capabilities with device constraints
- Implement secure execution paths, model protection, and integrity verification on edge devices
- Develop benchmarking suites that characterize accuracy, latency, and energy trade-offs across devices
- Drive responsible AI considerations including on-device privacy and bias evaluation
- Maintain comprehensive, current technical documentation — including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures — so that the system remains supportable, auditable, and easy to onboard new engineers onto over time
- Stay current 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 the team
Skills
- Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related 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 framework
- 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 privacy and security 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
- Open-source contributions to edge AI frameworks
- Experience optimizing LLMs for on-device inference
Benefits
- Competitive base salary commensurate with experience, plus benefits.
- Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
- Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
- We will support H1B transfers for qualified candidates.
Company Overview