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Oculus Vr Jobs (NOW HIRING)

Charles River Analytics

UX Software Engineer

Cambridge, MA · Hybrid

$100K - $200K/yr

Oculus Quest, Hololens, HTC Vive or other Steam VR HMDs What you need * Ability to work in a Hybrid (60%, 3x days per week) onsite capacity in Cambridge, Massachusetts * Bachelor's degree in computer ...

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How much do oculus vr jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for oculus vr in the United States is $46.24, according to ZipRecruiter salary data. Most workers in this role earn between $40.14 and $50.72 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Oculus Vr position, and why are they important?

To thrive in an Oculus VR-related role, you typically need expertise in virtual reality development, 3D modeling, programming (such as C#, C++, or Unity), and a solid understanding of immersive technologies. Familiarity with Oculus SDKs, VR hardware, version control systems, and VR simulation or game engines is highly valued, and certifications in VR development can be a plus. Strong problem-solving skills, creativity, and the ability to collaborate within multidisciplinary teams help professionals deliver engaging and user-friendly VR experiences. These skills and qualities are essential to keep up with the rapidly evolving VR landscape and ensure the development of innovative and high-quality Oculus VR applications.

What is an Oculus VR job?

An Oculus VR job involves working with Meta's virtual reality technology to develop, improve, or support VR hardware, software, and experiences. Roles can range from engineering and design to marketing and customer support. Employees may work on projects such as game development, VR applications, hardware innovations, or user experience improvements. These positions require skills in VR development, 3D modeling, programming, or related fields, depending on the specific role.

What does a typical workday look like for someone in an Oculus VR development role?

A typical day for an Oculus VR developer involves collaborating with designers and artists to plan and implement immersive VR experiences, writing and testing code in platforms like Unity or Unreal Engine, and troubleshooting performance or user interface issues on Oculus hardware. Team members often attend stand-up meetings to align on project goals and brainstorm solutions for technical challenges. Regular interaction with quality assurance, product managers, and other specialists ensures that the VR applications meet user expectations and hardware compatibility standards. This dynamic environment requires adaptability, strong teamwork, and continuous learning to stay current with VR advancements.

More about Oculus Vr jobs
What cities are hiring for Oculus Vr jobs? Cities with the most Oculus Vr job openings:
What are the most commonly searched types of Oculus Vr jobs? The most popular types of Oculus Vr jobs are:
What states have the most Oculus Vr jobs? States with the most job openings for Oculus Vr jobs include:
What job categories do people searching Oculus Vr jobs look for? The top searched job categories for Oculus Vr jobs are:
Oculus Vr jobs near you
Infographic showing various Oculus Vr job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $96,184 per year, or $46.2 per hour.
Senior Firmware Engineer, Edge AI / NPU Runtime

Senior Firmware Engineer, Edge AI / NPU Runtime

Tacit

San Francisco, CA • On-site

$150K - $200K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago

Job description

About Tacit
We are an early-stage, deep tech startup based in San Francisco, developing innovative hardware that rethinks human-computer interaction. We are backed by General Catalyst, Khosla Ventures, and Greylock Partners, with a founding team from Stanford, BrainGate, Oculus, and Tesla. While we can't reveal too much just yet, our team is tackling cutting-edge engineering challenges to bring revolutionary products to life.
About the role
We're looking for a Senior Firmware Engineer, Edge AI / NPU Runtime to help architect, optimize, and ship next-generation neurotech hardware with production-grade on-device intelligence. You will own critical parts of the embedded AI stack, from realtime sensor acquisition through preprocessing, NPU/DSP-accelerated inference, postprocessing, telemetry, and product deployment.
This is a hands-on role for someone who wants to work close to the hardware while shaping the intelligence users experience in the product. You'll help define how models run on-device, how sensor data moves through the system, and how we meet tight latency, reliability, and power budgets in real-world use.
What you'll do
  • Edge AI & NPU Inference
    • Own deployment of ML models onto embedded targets using NPUs, DSPs, MCUs, or other hardware accelerators.
    • Integrate embedded inference runtimes, vendor NPU/DSP SDKs, and model deployment workflows into production firmware.
    • Optimize inference latency, memory footprint, throughput, power consumption, and accelerator utilization on production hardware.
    • Partner with ML teams on quantization, operator support, model architecture tradeoffs, calibration datasets, and accuracy/performance regressions.
  • Realtime Sensor-to-Inference Systems
    • Build realtime sensor-to-inference pipelines, including acquisition, timestamping, synchronization, preprocessing, feature extraction, model execution, and postprocessing.
    • Design low-latency data movement using DMA, interrupts, ring buffers, deterministic scheduling, and efficient memory layouts.
    • Support streaming inference patterns such as sliding windows, temporal models, event-driven execution, and continuous sensor processing.
    • Maintain inference quality and timing guarantees under real-world conditions such as sensor noise, clock drift, dropped samples, variable system load, and power-state transitions.
  • Power-Optimized Embedded Firmware
    • Optimize end-to-end energy per inference across sensing, preprocessing, model execution, postprocessing, and idle time.
    • Use low-power firmware techniques such as sleep states, duty cycling, subsystem power gating, clock scaling, batching/windowing, and dynamic power management.
    • Profile and improve power consumption across sensors, CPU, NPU/DSP, memory, and supporting firmware infrastructure.
  • Product Quality & Debugging
    • Bring up and debug firmware across sensors, accelerators, power systems, embedded compute, and production hardware.
    • Use lab tools, traces, logs, telemetry, and instrumentation to root-cause complex embedded system issues.
    • Translate product and customer experience goals into concrete latency, reliability, responsiveness, and power targets.
    • Build diagnostics, validation hooks, and performance benchmarks to ensure reliable real-world edge inference behavior.
Requirements
  • 5+ years of experience in embedded firmware, embedded systems, or edge ML systems.
  • Strong C/C++/Rust experience on resource-constrained embedded platforms.
  • Experience with RTOS-based systems such as FreeRTOS, Zephyr, ThreadX, or similar.
  • Experience deploying or optimizing ML inference on embedded targets, NPUs, DSPs, MCUs, or edge SoCs.
  • Strong understanding of realtime embedded systems, including DMA, interrupts, concurrency, memory management, and low-latency data movement.
  • Experience optimizing embedded systems for latency, memory footprint, throughput, and power consumption.
  • Hands-on debugging and bring-up experience across embedded hardware and firmware systems, with strong cross-functional communication across firmware, ML, electrical, software, and product teams.
Strong candidates may have
  • Experience with embedded inference runtimes, deployment toolchains, or edge AI SoCs/accelerators such as TensorFlow Lite Micro, ONNX Runtime, CMSIS-NN, Qualcomm QNN/SNPE, ARM Ethos-U/Vela, TVM, ExecuTorch, Qualcomm, ARM, Cadence/Tensilica, Syntiant, Ambiq, Nordic, NXP, ST, Hailo, Google Edge TPU, or similar.
  • Experience with quantized inference, fixed-point math, SIMD/DSP optimization, accelerator programming, or model conversion workflows.
  • Experience with streaming or time-series ML workloads such as biosignals, sensor fusion, audio, gesture recognition, keyword spotting, or other realtime inference systems.
  • Experience shipping battery-powered consumer electronics, wearable, neurotech, AR/VR, robotics, camera, IoT, or other embedded AI products.

Compensation Range
$150,000 - $200,000/year
Benefits
  • Competitive equity package
  • Comprehensive medical, dental, and vision insurance
  • Company size: 20-30 people
  • Unlimited PTO
  • Visa sponsorship
  • 3% 401k matching

Apply