Senior Embedded Video Analytics Engineer-Onsite

Cognizant; Irving (TX); On-site; USD 95,000 - 118,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

Paid holidays plus Paid Time Off

401(k) plan and contributions

Long‑term/Short‑term Disability

Paid Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant’s IoT Practice seeks an engineer to port and optimize a containerized video analytics pipeline for CPU‑constrained routers. You’ll own model optimization, container architecture, on‑device inference, and performance tuning on Cradlepoint OS/PrplOS hardware.

Required skills include embedded systems, Docker/LXC, and CV model optimization (quantization, ONNX, TensorFlow Lite). Onsite role in Texas with strong compensation and benefits. Visa sponsorship not available.

Qualifications

• 4+ years in embedded systems or edge ML deployment.
• Experience with containerization (Docker, LXC) on constrained devices.
• ML model optimization via quantization, pruning, ONNX, TensorFlow Lite, OpenVINO.
• Video analytics / computer vision (YOLO variants, object detection pipelines).
• Python + C/C++ on Linux embedded targets.
• Cross‑compilation, profiling, and memory optimization.

Responsibilities

• Port GPU‑based video analytics models to CPU‑only router targets.
• Optimize inference pipeline to stay under 100MB memory footprint using SLMs.
• Build containerized architecture with dynamic cloud‑driven model loading.
• Tune accuracy/performance tradeoffs on ARM/MIPS router hardware.
• Integrate with Cradlepoint OS and PrplOS environments.
• Benchmark and iterate on detection accuracy vs. latency on constrained hardware.

Skills

Embedded systems

Edge ML deployment

Python

C/C++

Cross-compilation

Profiling

Memory optimization

YOLO / CV pipelines

Quantization

Pruning

ONNX

TensorFlow Lite

OpenVINO

Video analytics

Tools

Docker

LXC

Job description

Role

Port and optimize a containerized video analytics pipeline to run on CPU-constrained router hardware (Cradlepoint OS, Wi‑Fi 7 PrplOS, FWA routers). You'll own the full stack: model optimization, container architecture, and on‑device inference performance.

What You’ll Do

• Port GPU‑based video analytics models (object detection, classification) to CPU‑only router targets
• Optimize inference pipeline to stay under 100MB memory footprint using SLMs
• Build containerized architecture with dynamic cloud‑driven model loading
• Tune accuracy/performance tradeoffs on ARM/MIPS router hardware
• Integrate with Cradlepoint OS and PrplOS environments
• Benchmark and iterate on detection accuracy vs. latency on constrained hardware

Required

• 4+ years in embedded systems or edge ML deployment
• Experience with containerization (Docker, LXC) on constrained devices
• ML model optimization: quantization, pruning, ONNX, TensorFlow Lite, OpenVINO
• Video analytics / computer vision (YOLO variants, object detection pipelines)
• Python + C/C++ on Linux embedded targets
• Cross‑compilation, profiling, and memory optimization

Strong Plus

• Cradlepoint NetCloud / PrplOS / OpenWRT experience
• NPU/DSP acceleration on router‑class SoCs
• DeepStream or similar inference pipeline experience (GPU→CPU migration)
• SLM deployment (sub‑1B parameter models on edge)
• RTSP/video streaming on embedded Linux

You Are

• Comfortable with no GPU — CPU‑only inference is the constraint, not a fallback
• Pragmatic about accuracy tradeoffs at the edge
• Experienced navigating vendor OS lock‑in and limited debugging toolchains

About Cognizant’s IoT Practice:

Intelligent, IoT‑enabled products will soon result in the proliferation of data and disrupt virtually all industries. To be successful, both large and small companies must leverage IoT capabilities by designing modern products that fundamentally connect people with processes. Within Cognizant IOT, we engineer industry‑aligned, IoT‑enabled products that merge industry needs with human drivers. Our intelligent products will revolutionize experiences and result in exciting, transformative outcomes. Without human‑centered thinking, connected products are just standalone things — but with it, our modern connected products facilitate a unified way of life enjoyed by all.

*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*

Compensation & Benefits

$95,000– $118,000 per year + Cost of Living Allowance

Bonus + Comprehensive Benefits

Additional Information

• Applications will be accepted until Sep 30, 2026
• Onsite role
• Visa sponsorship is not available now or in the future. Candidates requiring sponsorship will not be considered.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long‑term/Short‑term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan