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Overnight Ai Data Collection Jobs in Oregon (NOW HIRING)

Principal Software Engineer, AI

OR · On-site +1

$134K - $180K/yr

Build the technical vision and roadmap for our Context Layer: a collection of high-quality data products - including a knowledge graph, RAG engines, and retrieval/search infrastructure - that give AI ...

ZENA | FSE: 49Q) is a technology company specializing in AI drones, Drone-as-a-Service (DaaS ... Certify results from data obtained from multiple data collection methods. Qualifications * Bachelor ...

New

On-site data collection for model training and validation * R&D visits to one of our in-person ... Experience using AI-assisted development tools thoughtfully to improve productivity, quality, and ...

Senior Prompt Designer II

OR · On-site +1

$101K - $108K/yr

... AI content teams. What's good to have * Experience with resume builder products, HR tech, or career content platforms * Familiarity with fine-tuning, RLHF, or preference data collection workflows

Accounts Receivable Specialist

OR · On-site +1

$60K - $70K/yr

Stratify collection activities to maximize cash receipts * Issue dunning letters to overdue ... Placer.ai's $100M round C funding (unicorn valuation!) * See our data in action at The Anchor

... data collection, and analysis to ensure working silicon What we need to see: BS/MS/PhD (or ... More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a ...

Showing results 41-60

Overnight Ai Data Collection information

What is an overnight AI data collection specialist?

An Overnight AI Data Collection job involves gathering and organizing data during nighttime hours to support the development and training of artificial intelligence systems. Workers in this role may collect images, audio, text, or other types of data, ensuring accuracy and quality according to specific guidelines. The overnight schedule helps companies process large volumes of data continuously and meet tight deadlines. This role is important for improving the performance and reliability of AI models. It often requires attention to detail, basic computer skills, and the ability to work independently.

What are the key skills and qualifications needed to thrive as an overnight AI data collection specialist?

To thrive as an Overnight AI Data Collection Specialist, you need strong attention to detail, data entry proficiency, and familiarity with data collection methodologies, often supported by a high school diploma or equivalent. Experience with data management tools, spreadsheets, and platforms such as SQL databases or Python scripts is commonly required. Reliability, time management, and effective communication are valuable soft skills for working independently during overnight shifts and ensuring data accuracy. These skills and qualities are essential to maintaining high data quality and supporting robust AI model development in a time-sensitive environment.

What are some common challenges faced by overnight AI data collection specialists, and how can they be managed?

Overnight AI data collection specialists often face challenges such as managing fatigue due to unconventional working hours and ensuring data accuracy during less supervised shifts. It’s important to establish a consistent sleep schedule and take regular breaks to maintain focus. Collaboration with daytime teams through detailed handover notes and communication tools helps ensure continuity and data integrity. Many organizations provide training and support to help manage these challenges and maintain high data quality.

What is the difference between Overnight Ai Data Collection vs Data Annotator?

AspectOvernight Ai Data CollectionData Annotator
CredentialsHigh school diploma or equivalent; basic computer skillsHigh school diploma or equivalent; attention to detail
Work EnvironmentRemote or on-site, flexible hours, often overnight shiftsRemote or on-site, regular hours, focused on labeling data
Industry UsageUsed in AI training data collection, especially for image and video dataUsed in AI model training, labeling datasets for machine learning

Overnight Ai Data Collection involves gathering raw data for AI training, often during overnight hours, while Data Annotator focuses on labeling and annotating existing datasets. Both roles are essential in AI development, with overlapping skills but different primary tasks.

How to be an Overnight AI Data Collection?

To work as an Overnight AI Data Collector, you should have strong attention to detail, basic computer skills, and the ability to work flexible hours. The role typically involves gathering, labeling, or verifying data for AI training during overnight shifts, often requiring familiarity with data management tools. Prior experience in data entry or similar tasks can be beneficial, and some positions may require completing a short training or assessment.

What are the most commonly searched types of Ai Data Collection jobs in Oregon?

The most popular types of Ai Data Collection jobs in Oregon are:

What are popular job titles related to Overnight Ai Data Collection jobs in Oregon?

For Overnight Ai Data Collection jobs in Oregon, the most frequently searched job titles are:

What cities in Oregon are hiring for Overnight Ai Data Collection jobs?

Cities in Oregon with the most Overnight Ai Data Collection job openings:

Senior Machine Learning Engineer, Perception - Autonomous Driving

Nvidia

OR • On-site, Remote

$104K - $143K/yr

Full-time

Posted 5 days ago


Key responsibilities

  • Design end-to-end perception solutions for autonomous driving to enable road network detection across various environments.

  • Develop and productize perception modules, including static-world tasks such as lane graph construction, road boundary detection, and traffic element recognition.

  • Collaborate with data collection and labeling teams to improve perception system accuracy through data-driven development and leverage simulation and augmentation for extreme scenarios.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA's GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world.

We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will be driving E2E solutions for perception modules that are responsible for online mapping - including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

What You'll Be Doing: Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways. Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks. Develop generalizable approaches to support diverse ODDs and Country/region expansion Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy.

Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized Leverage data simulation and augmentation for solving extreme scenarios Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness. What We Need to See: Minimum Requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.

Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch). Experience in data-driven development and collaboration with data and ground truth teams. Strong programming skills in python and/or C++

Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other. Ways to Stand Out from the Crowd: Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras. Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.

Proven expertise in deep learning backed up by technical publications in leading conferences/journals. Expertise with Transformers, BEV architectures, and modern static-world perception techniques.Experience in working on similar online mapping and complex road detection problems is a big plus. Intelligent machines powered by AI are no longer science fiction

GPU Deep Learning has made it possible for self-driving cars to learn, perceive, and reason about the world. NVIDIA GPUs power the algorithms that enable both static world understanding and scalable perception across global road systems. Join us and help define the future of reliable, data-driven autonomous driving.

#AutonomousVehicles Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 2, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US