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Sick Sensor Jobs in Seattle, WA (NOW HIRING)

TASi Measurement

Marketing Manager

Kent, WA · On-site

Seametrics is a designer and manufacturer of a variety of flow metering and submersible sensor ... What We Offer: * Competitive salaries * 10 paid holidays each year, vacation, sick time and ...

Seattle Metrics Inc.

Marketing Manager

Kent, WA · On-site

Seametrics is a designer and manufacturer of a variety of flow metering and submersible sensor ... What We Offer: * Competitive salaries * 10 paid holidays each year, vacation, sick time and ...

MAGNIX USA INC

Technician

Everett, WA · On-site

$37 - $45/hr

... sensor installation, fluid and electrical connections, and fixture installation. * Set up ... sick time, and 11 paid holidays. * 401K retirement plan with industry leading 9.5% company ...

Waymo

Senior Research Scientist, Perception

Kirkland, WA · On-site

$213K - $263K/yr

Integrate emerging research from the broader AI community into Waymo's Encoders and Sensor ... Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) * Maternity ...

Waymo

Senior Software Engineer, Model Lifecycle

Kirkland, WA · Hybrid

$139K - $183K/yr

Design, build, and maintain scalable data pipelines to process many petabytes of complex sensor ... Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary) * Maternity ...

Amphenol TCS

Signal Integrity Engineer

Seattle, WA · On-site

$95K - $150K/yr

... sensor-based products and coaxial and high-speed specialty cable. ACS has an expansive global ... day 1, vacation, sick leave, personal days, paid holidays, life insurance, short/long term ...

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All JobsSick Sensor JobsSick Sensor Jobs in Seattle, WA

Sick Sensor information

See Seattle, WA salary details

$14

$27

$44

How much do sick sensor jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for sick sensor in Seattle, WA is $27.81, according to ZipRecruiter salary data. Most workers in this role earn between $20.53 and $34.76 per hour, depending on experience, location, and employer.

What is the difference between Sick Sensor vs Industrial Automation Technician?

AspectSick SensorIndustrial Automation Technician
CertificationsSensor-specific training, electrical certificationsElectronics, PLC programming, electrical certifications
Work EnvironmentManufacturing plants, industrial settingsFactories, automation systems, maintenance facilities
Industry UsageSensor installation and calibration in automationMaintaining and troubleshooting automation equipment

While Sick Sensors focus on installing and calibrating sensors within industrial systems, Industrial Automation Technicians handle broader tasks including troubleshooting, programming, and maintaining automation equipment. Both roles require electrical knowledge and work in manufacturing environments, but the Sensor role is more specialized in sensor technology, whereas the Technician covers a wider range of automation systems.

What are popular job titles related to Sick Sensor jobs in Seattle, WA? For Sick Sensor jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Sick Sensor jobs in Seattle, WA look for? The top searched job categories for Sick Sensor jobs in Seattle, WA are:
Sick Sensor jobs near you

Senior AI Inference Engineer - Model Optimization & Deployment

Zoox

Seattle, WA

$242K - $290K/yr

Full-time

Medical, Life, PTO

Posted 17 days ago

Job description

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence.

As a Model Optimization & Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex models (LLMs, VLMs, or FMs) for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices.
In this role, you will:
  • Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA).
  • Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment.
  • Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries.
  • Develop and optimize custom ML OPs and TensorRT Plugins with efficient CUDA kernels to minimize latency and maximize memory bandwidth on AI accelerators.
  • Write production-level, low latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems.
Qualifications:
  • Deep expertise in model quantization (PTQ, QAT) and mixed-precision inference frameworks (INT8, FP8, FP4, BF16/FP16).
  • Proven experience optimizing large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs/VLAs) utilizing Efficient Attention mechanisms (e.g., FlashAttention, Linear Attention), KV-cache optimization (e.g., PagedAttention) and Speculative Decoding.
  • Extensive experience with model conversion/compilation pipelines (e.g., ONNX, TensorRT, torch.compile) and performing rigorous latency benchmark and model quality parity valuation.
  • Proficiency in low-level programming for AI accelerators, specifically developing and optimizing custom ML OPs and TensorRT Plugins with efficient CUDA kernel implementations.
  • Production-level C++ (14/17/20) and Python programming skills, with experience developing concurrent, memory-safe, real-time inference code for edge devices.
Bonus Qualifications:
  • Familiarity with SOTA autonomous driving perception algorithms (temporal 3D object detection, BEV, 3D Occupancy Networks) and multi-modal sensor processing (Vision, LiDAR, Radar).
  • Experience with distributed training pipelines and model/tensor parallelism (PyTorch Distributed, Ray, DeepSpeed, Megatron-LM) and runtime efficiency optimization for GPU clusters.
  • Experience with end-to-end autonomous driving paradigms (VLM/VLA models, Foundation models) and edge deployment technologies (e.g., TensorRT-LLM).
$242,000 - $290,000 a year
Base Salary Range
 
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
 
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations
If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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