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Russian Data Annotation Manager Jobs in Michigan

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99.60K - $135.20K/yr

... manual annotation costs. · Enable simulation-to-real (Sim2Real) data workflows, including domain randomization and synthetic data generation. · Manage data versioning, metadata, and dataset ...

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Russian Data Annotation Manager information

What is a Russian Data Annotation Manager job?

A Russian Data Annotation Manager oversees the process of labeling and annotating data in the Russian language for machine learning and AI projects. They manage teams of annotators, ensure data quality, and optimize workflows to meet project requirements. This role requires fluency in Russian, attention to detail, and experience with annotation tools. Additionally, they collaborate with engineers and linguists to refine annotation guidelines for accurate model training.

What are the key skills and qualifications needed to thrive in the Russian Data Annotation Manager position, and why are they important?

To thrive as a Russian Data Annotation Manager, you need fluency in Russian, experience with data annotation processes, and strong organizational abilities, often supported by a background in linguistics, computer science, or a related field. Familiarity with annotation platforms, data labeling tools, and project management software is commonly required. Leadership, attention to detail, and effective communication are key soft skills that help excel in managing diverse annotation teams. These skills are essential for ensuring high-quality data outputs and efficient project delivery in multilingual technology environments.

What are some common challenges faced by Russian Data Annotation Managers, and how do they overcome them?

Russian Data Annotation Managers often encounter challenges related to maintaining consistency and accuracy across large, multilingual annotation teams, especially when dealing with nuanced language data. They address these issues by developing clear guidelines, conducting regular quality checks, and providing ongoing training to annotators. Collaboration with data scientists, project managers, and quality assurance personnel is also important to quickly resolve ambiguities and implement feedback. By fostering open communication and setting clear expectations, managers help ensure project standards are met and team members feel supported.
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Senior Robotics Data Collection Engineer - Only W2

Saransh Inc

Warren, MI • On-site

$99.60K - $135.20K/yr

Contractor

Posted 22 days ago


Job description

Role: Senior Robotics Data Collection Engineer
Location: Warren, MI (Onsite from Day 1)
Job Type: W2 Contract
 
Main Skills: Senior Robotics Data Collection Engineer (MLE, Python, Cloud exp, Linux)
 
Key Responsibilities:
· Collect high-quality robot telemetry, sensor, and visual data from manufacturing robotic systems in lab and production-like environments.
· Operate and monitor robotic systems, GELLO teleop interfaces, and data collection hardware.
· Organize, label, and validate data according to established annotation guidelines and quality standards.
· Perform manual annotation and verification when necessary to generate high-quality ground truth labels.
· Execute data collection campaigns following documented protocols and experimental designs.
· Troubleshoot data collection issues and document problems for engineering teams.
· Collaborate with AI engineers, robotics engineers, and manufacturing teams to ensure data meets model training requirements.
 
Required Qualifications:
· College or bachelor’s degree in engineering (Mechanical Engineering or Electrical Engineering preferred).
· Attention to detail and ability to follow technical procedures and documentation.
· Strong, demonstrated hands-on experience operating, troubleshooting, and maintaining industrial or collaborative robotic arms.
· Proficiency in Linux environments and basic scripting (e.g., Python) to interface with robotic systems and manage data pipelines.
· Proven experience working directly with perception sensors and hardware, with a solid understanding of capturing and validating high-quality sensor data.
 
Preferred Qualifications:
· Experience with robotics, manufacturing, or data collection.
· Familiarity with Python, Linux, or data tools (beneficial but not required).
· Experience operating or troubleshooting technical equipment.
· Basic understanding of machine learning, AI, or data annotation concepts.
· Experience in automotive or manufacturing environments.