Embedded AI Engineer

Bright Vision Technologies; Highlands Ranch (CO); Remote; USD 100.000 - 150.000; Vollzeit

Zusammenfassung

Bright Vision Technologies is seeking an Embedded AI Engineer to design, optimize, and deploy ML models for edge devices and mobile platforms. You will work across hardware constraints, implement privacy-respecting telemetry, and ensure reliable on-device AI capabilities outside data centers.

The role requires deep expertise in model compression, quantization, and hardware-aware optimization, with production deployment experience on mobile/embedded systems.

Qualifikationen

• 6+ years of ML engineering with edge or mobile AI.
• Strong Python and C++ proficiency.
• Experience with model compression, quantization, and pruning.
• Experience with at least one major edge inference framework.
• Solid understanding of mobile/embedded hardware architectures.
• Experience deploying ML models to production on mobile/embedded platforms.
• Strong performance engineering and profiling skills.
• Familiarity with on-device privacy and security considerations.
• Strong communication and cross-functional collaboration skills.

Aufgaben

• Design edge AI solutions for mobile SoCs, NPUs, and accelerators.
• Apply compression and optimization to fit edge constraints.
• Tune latency, energy and memory on target hardware.
• Build cross-platform runtimes with TF Lite, ONNX Runtime, Core ML.
• Optimize models for accelerators including DSPs/GPUs.
• Implement on-device updates, versioning, and rollback workflows.
• Design hybrid edge-cloud architectures with variable connectivity.
• Build telemetry respecting privacy for continuous improvement.
• Collaborate with hardware, firmware, and product teams.
• Ensure secure execution paths and model protection on edge devices.
• Develop benchmarking suites for accuracy, latency, energy.
• Drive responsible AI with on-device privacy and bias checks.
• Maintain architecture docs, runbooks, and technical references.

Kenntnisse

6+ years ML edge/mobile AI

Python & C++

Model compression/quantization/pruning

Major edge inference frameworks

Mobile/embedded hardware knowledge

Production deployment on mobile/edge

Performance engineering & profiling

On-device privacy & security awareness

Cross-functional communication

Ausbildung

Bachelor’s or Master’s in CS/CE or related field

Tools

TensorFlow Lite

ONNX Runtime

Core ML

Jobbeschreibung

Embedded AI Engineer - Remote

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.

Job Title: Embedded AI Engineer

Location: 100% Remote (U.S.)

Position Type: Full-time, Direct W2

Salary Range: $100,000–$150,000 Annually

Experience Required: 6+ years

Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.

Job Summary

We are looking for an Embedded AI Engineer to design, optimize, and deploy machine learning models that run efficiently on resource-constrained edge devices, including mobile platforms, embedded systems, and specialized accelerators. 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. The ideal candidate has shipped edge AI in production environments where compute, memory, energy, and connectivity constraints fundamentally shape the engineering trade-offs.

Key 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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.

Bright Vision Technologies is an Equal Opportunity Employer.

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.