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Data Annotation Research Jobs in Bothell, WA (NOW HIRING)

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Data Annotation Research information

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

What are popular job titles related to Data Annotation Research jobs in Bothell, WA? For Data Annotation Research jobs in Bothell, WA, the most frequently searched job titles are:
What cities near Bothell, WA are hiring for Data Annotation Research jobs? Cities near Bothell, WA with the most Data Annotation Research job openings:
Member of Technical Staff, Microsoft Robotics (Spatial AI)

Member of Technical Staff, Microsoft Robotics (Spatial AI)

Microsoft

Redmond, WA • On-site

Full-time

Posted 2 days ago


Microsoft rating

8.6

Company rating: 8.6 out of 10

Based on 125 frontline employees who took The Breakroom Quiz

46th of 184 rated software companies


Job description

Overview
Microsoft's Discovery and Quantum (MDQ) division develops and delivers advanced artificial intelligence (AI), cloud-enabled capabilities, and strategic technologies to help solve the world's major challenges. From accelerating scientific discovery with advanced AI tools, to pioneering breakthroughs in quantum computing, to advancing robotics and AI capabilities that drive real-world impact, joining MDQ means building the future, partnering with fast-moving innovators, and operating in a high-impact, mission-driven environment.
At Microsoft Robotics within MDQ, we build and deploy technologies that enable people, robots, and AI agents to collaborate and achieve more.
We are building Microsoft's platform for physical intelligence-an integrated robotics software and AI platform that brings together humans, robots, and agents through robotics AI models, innovative teaming solutions and experiences, physically grounded agentic AI workflows, trustworthy test and evaluation, and real-world customer-focused validation. Built on Microsoft's core platforms and delivered through and with a global ecosystem of partners and customers, this platform accelerates AI for the physical world and helps robotics solutions move from experimentation to reliable, scaled deployment.
We are hiring a Member of Technical Staff, Microsoft Robotics (Spatial AI) at the data & applied science II level, to design, develop, and test physical world models that enable robots to understand, predict, and reason about the 3D physical environments in which they operate. This role focuses on building models that capture spatial structure, object relationships, physics dynamics, and scene semantics, providing robots with the physical intuition needed for manipulation, navigation, and interaction planning. The engineer will work at the frontier of world modeling, spatial AI, and foundation models for robotics, contributing to models that predict how the physical world changes in response to robot actions and environmental dynamics.
Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
#MicrosoftRobotics #MDQ
Responsibilities
  • Design, develop, and evaluate physical world models that capture 3D spatial structure, object geometry and pose, physics dynamics, material properties, and semantic scene understanding for robotic applications.
  • Build and train world models (e.g., video prediction models, neural physics simulators, 3D generative models, scene graph representations) that predict future states of physical environments conditioned on robot actions, enabling model-based planning and policy learning.
  • Develop spatial AI capabilities including 3D scene reconstruction, object detection and pose estimation, spatial relationship reasoning, occupancy prediction, and dense 3D feature representations for robot perception and planning.
  • Implement and maintain evaluation frameworks for world models and spatial AI systems, including prediction accuracy metrics, planning performance benchmarks, and generalization testing across environments and object categories.
  • Collaborate with robotics researchers, learning engineers, and simulation engineers to integrate world models into robot planning and control pipelines, enabling model-predictive control, imagination-based planning, and data-augmented training.
  • Build data pipelines for training world models, including multi-sensor data fusion (RGB, depth, LiDAR, proprioception), scene annotation, and dataset curation for diverse physical environments and interaction scenarios.
  • Write efficient, readable, extensible code in Python (including PyTorch, JAX, or TensorFlow) for model development, training, and evaluation, leveraging GPU computing infrastructure for large-scale experiments.
  • Contribute to the formulation of the team's world modeling research and development roadmap, identifying high-impact technical directions and collaborating with leadership to prioritize investments.
  • Present research findings and model evaluation results clearly and efficiently to internal stakeholders and external partners, contributing to technical publications, blog posts, and conference presentations.
  • Stay current with state-of-the-art research in world models, spatial AI, 3D vision, neural physics simulation, and foundation models for physical understanding, actively contributing to the body of thought leadership in these areas.

Qualifications
Required Qualifications:
  • Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
    • OR equivalent experience.

Other Requirements:
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings
    • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:
  • Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience.
  • Strong background in robotics perception, navigation, and proprioceptive sensor stacks and systems integration, including algorithm and model development and implementation in real-world applications.
  • Experience with world models, video prediction models, neural physics simulators, or generative 3D models for physical environment understanding and prediction.
  • Strong background in 3D computer vision, including depth estimation, 3D reconstruction, NeRF/Gaussian splatting, point cloud processing, or spatial reasoning.
  • Proficiency in PyTorch, JAX, or TensorFlow with experience training large-scale models on GPU clusters (Azure Machine Learning, Kubernetes, or equivalent).
  • Experience with robotics perception systems, including multi-sensor fusion (RGB-D, LiDAR, proprioception), object pose estimation, or scene graph construction.
  • Familiarity with model-based reinforcement learning, model-predictive control, or imagination-based planning approaches that leverage learned world models.
  • Published research or demonstrated contributions to world models, spatial AI, 3D vision, neural simulation, or physical AI in top-tier venues (NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, ECCV, or equivalent).
  • Experience with the Microsoft Azure AI toolset (Azure Machine Learning, Azure Databricks, Azure Cognitive Services) or equivalent cloud ML platforms.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800.00 - $219,200.00 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

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Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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