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Full Time Machine Learning Data Annotation Jobs in Pennsylvania

Guru Schools

Machine Learning Engineer

Philadelphia, PA · On-site

Machine Learning Engineer Philadelphia, PA OR Washington, DC | Hybrid: 3-4 days/week 9 + Months ... Enhance existing AIML automation tools (e.g., Speech data), implement LLM prompt interactions, and ...

TeleTracking

Machine Learning Engineer III

Pittsburgh, PA · On-site

... data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions. • Work with large ...

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

... data, completely digitizing workflows that have historically been manual and error-prone. This ... About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ...

Gather AI

Director of Machine Learning

Pittsburgh, PA

... data, completely digitizing workflows that have historically been manual and error-prone. This ... About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ...

Motional

Staff Machine Learning Engineer

Pittsburgh, PA · On-site +1

Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and ...

Motional

Staff Machine Learning Engineer

Pittsburgh, PA · On-site

Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Pennsylvania

Full Time Machine Learning Data Annotation information

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Pennsylvania? For Full Time Machine Learning Data Annotation jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Pennsylvania look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Full Time Machine Learning Data Annotation jobs? Cities in Pennsylvania with the most Full Time Machine Learning Data Annotation job openings:
Full Time Machine Learning Data Annotation jobs near you
Staff AI Engineer, Perception

Staff AI Engineer, Perception

Agility Robotics

Pittsburgh, PA

$207K - $323K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 24 days ago

Job description

Agility's commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.

Agility Robotics is deploying humanoid robots that are solving real-world challenges in logistics and manufacturing. Perceiving and understanding the world is critical to Digit's success in these applications. The Perception team is looking for a staff machine learning engineer to own the design and development of object detection and tracking algorithms.

Responsibilities:

  • As a technical lead, you will own the architecture and technical roadmap for object perception systems used by the robot in production
  • Design, develop, and deploy machine learning algorithms for multi-object detection, scene understanding, and 6-DoF object pose estimation
  • Evaluate and drive adoption of state-of-the-art perception models
  • Promote best practices in architecture, design, and testing to deliver high-quality, scalable software
  • Optimize deep neural networks and associated data processing to run efficiently on embedded systems
  • Collaborate with navigation, manipulation and hardware teams to align perception capabilities with product requirements

Requirements:

  • 5+ years of experience deploying machine learning-based object detection algorithms on mobile robots with at least 2 years of experience in a technical leadership role
  • Proficiency in related technical areas such as (but not limited to) deep convolutional neural networks, multi-object tracking, data association, supervised learning and pose estimation
  • Strong mathematical fundamentals in linear algebra and numerical optimization and familiarity with core geometric concepts in computer vision
  • Familiarity with common computer vision and machine learning libraries such as (but not limited to) PyTorch, OpenCV, NumPy, etc.
  • Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures
  • Experience with MLOps such as (but not limited to) data annotation services, data storage, model evaluation tools, and model deployment
  • Publications in your field (CVPR, ICCV, RSS, ICRA preferred)

Bonus Qualifications:

  • Experience using YOLO, Faster/Mask R-CNN
  • Experience developing ML models for 3 or 6 dof pose estimation

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Anticipated Salary Range
$207,000—$323,000 USD

In addition to base pay, our competitive total rewards package consists of the following for full-time employees:

  • 401(k) Plan: Includes a 6% company match.
  • Equity: Company stock options.
  • Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
  • Benefit Start Date: Eligible for benefits on your first day of employment.
  • Well-Being Support: Employee Assistance Program (EAP).
  • Time Off:
    • Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
    • Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
  • On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
  • Parental Leave: Generous paid parental leave programs.
  • Work Environment: A culture that supports flexible work arrangements.
  • Growth Opportunities: Professional development and tuition reimbursement programs.
  • Relocation Assistance: Provided for eligible roles.
  • Annual Discretionary Bonus: Provided for eligible roles.

All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.

Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.

Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.

Apply Now: https://grnh.se/b444bbd04us