CV/ML Systems Engineer, Hardware Architecture

Meta; Burlingame (CA); On-site; USD 250,000 - 350,000; Full time

Job summary

Meta Reality Labs in California seeks a principal-level CV/ML Systems Engineer to lead software integration onto hardware across the organization, driving end-to-end programs for CV/ML workloads on custom silicon and sensor subsystems powering next-generation VR/AR products.

You will orchestrate cross-functional teams, align silicon tape-out with software milestones, and define validation criteria to ensure real-time performance and efficiency in immersive spatial computing experiences.

Qualifications

• 12+ years of hardware systems architecture experience focusing on CV/ML workloads.
• Experience in SoC/system-level architecture for CV or ML inference workloads.
• Experience with hardware-software co-design for on-device CV/ML workloads.
• Ability to build performance models and evaluate real-time trade-offs at scale.
• Experience guiding silicon strategy across large teams in consumer electronics or spatial computing.

Responsibilities

• Drive organization-wide software integration programs onto hardware platforms with cross-functional teams.
• Define and own end-to-end program roadmap for CV/ML inference on VR/AR devices.
• Lead hardware-software co-design aligning software milestones with silicon tape-out schedules.
• Establish integration requirements and milestones translating perception demands into deliverables.
• Identify risks and bottlenecks, ensuring accountability across engineering groups.
• Coordinate with silicon, firmware, and platform teams to define architecture for CV/ML accelerators.
• Develop program tracking frameworks to measure progress and readiness.
• Engage with external silicon partners and sensor vendors to align timelines.
• Communicate status and trade-offs to executives through proposals and reviews.
• Define benchmarking and validation criteria for CV/ML software onto hardware.

Skills

Hardware systems architecture

CV/ML inference

SoC architecture

Cross-functional leadership

Performance modeling

Job description

About

Meta Reality Labs is seeking a principal-level CV/ML Systems Engineer to lead the integration of software programs onto hardware systems across the organization. In this role, you will drive end-to-end software integration programs spanning computer vision and machine learning workloads onto custom silicon, sensor subsystems, and hardware platforms powering next-generation virtual and augmented reality products. You will operate at the intersection of program leadership and technical architecture, orchestrating cross-functional efforts to deliver CV/ML capabilities onto hardware with the performance, efficiency, and latency required for immersive, real-time spatial computing experiences.

Responsibilities

• Drive organization-wide software integration programs onto hardware platforms, orchestrating cross-functional teams across silicon engineering, ML platform, perception algorithms, and hardware systems to deliver CV/ML capabilities on custom silicon
• Define and own the end-to-end program roadmap for integrating CV/ML inference pipelines onto VR headsets, AR glasses, and wearable spatial computing platforms across multiple product generations
• Lead hardware-software co-design initiatives by aligning software development milestones with silicon tape-out schedules, ensuring timely integration of perception algorithms onto target hardware
• Establish integration requirements, success criteria, and program milestones that translate perception algorithm demands into actionable deliverables across hardware and software teams
• Identify and resolve cross-functional dependencies, risks, and bottlenecks in software-to-hardware integration programs, driving accountability across engineering organizations
• Coordinate with silicon engineering, firmware, and platform teams to define architectural requirements for custom CV/ML accelerators and SoCs based on software integration needs
• Develop and maintain program tracking frameworks to evaluate integration progress, hardware readiness, and software maturity against real-world CV/ML workload requirements
• Engage with external silicon partners, sensor vendors, and IP providers to align integration timelines and ensure emerging CV/ML hardware technologies are incorporated into program plans
• Communicate program status, integration trade-offs, and roadmap decisions to executive leadership and cross-functional stakeholders through written proposals, program reviews, and status updates
• Define benchmarking methodologies and integration validation criteria for CV/ML software onto hardware systems across the full stack from sensor ingestion through algorithm execution

Minimum Qualifications

• 12+ years of experience in hardware systems architecture with a focus on computer vision, machine learning inference, or high-performance signal processing systems
• Experience defining SoC or system-level architecture for CV or ML inference workloads, including image signal processor pipelines, compute hierarchy design, memory subsystem architecture, and interconnect topology
• Experience with hardware-software co-design methodologies for on-device CV/ML workloads, including familiarity with ML compiler stacks, operator fusion, quantization impacts on hardware design, and perception algorithm profiling
• Experience developing system performance models and using simulation or analytical frameworks to evaluate architectural trade-offs for real-time CV/ML workloads at scale
• Track record of driving multi-year hardware architecture roadmaps and influencing silicon strategy across large engineering organizations in consumer electronics or spatial computing domains Background in collaborating with computer vision and ML research teams to translate novel perception model architectures into hardware-efficient deployment targets on custom silicon
• Experience architecting CV/ML inference systems for power- and area-constrained wearable or mobile devices, including VR headsets, AR glasses, or similar spatial computing platforms
• Experience evaluating and integrating emerging memory and sensor technologies into CV/ML system architectures, including event cameras, time-of-flight sensors, or near-sensor compute approaches
• Familiarity with perception workloads such as SLAM, depth estimation, hand and eye tracking, scene segmentation, or neural radiance field rendering and their specific hardware demands