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Remote Data Annotation information

What is a Remote Data Annotation job?

A Remote Data Annotation job involves labeling, tagging, or categorizing data (such as images, text, audio, or video) to help improve machine learning models. This work is typically done from home using specialized annotation tools provided by employers. Accuracy and attention to detail are essential, as the quality of annotations directly impacts AI model performance. Many companies hire remote annotators on a freelance, part-time, or contractual basis.

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

To thrive as a Remote Data Annotation specialist, strong attention to detail, accuracy, and familiarity with basic data processing concepts are essential, often requiring a high school diploma or equivalent. Experience using data labeling platforms, annotation tools (such as Labelbox or Supervisely), and sometimes familiarity with spreadsheet software may be required. Excellent time management, communication skills, and the ability to work independently are valuable soft skills in this remote role. These skills are vital to ensure that data annotations are consistent, precise, and delivered on schedule, which directly impacts the quality of AI and machine learning outcomes.

What are the typical daily tasks for someone working in Remote Data Annotation?

Daily tasks for a Remote Data Annotation role usually involve reviewing and labeling large volumes of data—such as images, audio clips, text, or video—according to specific project guidelines. You will use specialized annotation tools to identify objects, transcribe content, categorize information, or tag relevant features to support machine learning projects. Communication with project managers or quality assurance teams may be necessary for feedback and clarity on guidelines. Most roles also require regular self-checks for accuracy and the ability to meet productivity quotas or deadlines. This structure allows for a combination of focused individual work and occasional team collaboration to ensure project goals are met.
More about Remote Data Annotation jobs
What are the most commonly searched types of Data Annotation jobs in Cambridge, MA? The most popular types of Data Annotation jobs in Cambridge, MA are:
What job categories do people searching Remote Data Annotation jobs in Cambridge, MA look for? The top searched job categories for Remote Data Annotation jobs in Cambridge, MA are:
What cities near Cambridge, MA are hiring for Remote Data Annotation jobs? Cities near Cambridge, MA with the most Remote Data Annotation job openings:
Remote Data Annotation jobs near you
Infographic showing various Remote Data Annotation job openings in Cambridge, MA as of May 2026, with employment types broken down into 1% As Needed, 86% Full Time, 12% Part Time, and 1% Contract. Highlights an 40% Hybrid, and 60% Remote job distribution.

Mechanical Engineering Expert - AI Content Specialist

Alignerr

Boston, MA • On-site, Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Mechanical Engineering Expert — AI Training About The Role We're looking for mechanical engineering experts to help train and improve the next generation of AI models. Your deep technical knowledge will directly shape how AI reasons through complex engineering problems — from fluid dynamics and thermodynamics to structural mechanics and beyond. This is a unique opportunity to sit at the intersection of rigorous engineering and cutting‐edge AI research, working remotely on your own schedule with some of the world's leading AI labs.

Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design Advanced Engineering Problems — Create challenging, domain‐specific problems spanning FEA (Finite Element Analysis), heat transfer, kinematics, fluid mechanics, and material science to rigorously test AI performance. Author Ground‐Truth Solutions — Develop detailed, step‐by‐step technical solutions that serve as benchmark "golden" responses for AI model training and evaluation. Audit AI Reasoning — Critically evaluate AI‐generated outputs including CAD logic, thermodynamic proofs, and material specifications for technical accuracy, safety, and compliance with engineering standards (e.g., ASME, ISO).

Refine Model Thinking — Identify logical failures in AI reasoning such as incorrect force distributions, energy conservation violations, or flawed material assumptions — and provide structured feedback to improve model performance. Who You Are Pursuing or holding a Master's or PhD in Mechanical Engineering, Aerospace Engineering, or a closely related field. Strong foundational knowledge across core engineering domains: solid mechanics, fluid mechanics, thermodynamics, CAD/CAM, or manufacturing processes.

Able to communicate complex technical concepts and physical phenomena clearly and precisely in written form. Highly detail‐oriented — comfortable checking mathematical derivations, unit conversions, and physical system constraints. No prior AI experience required — your engineering expertise is what matters.

Nice to Have Experience with data annotation, data quality evaluation, or technical review workflows. Familiarity with engineering software such as SolidWorks, MATLAB, or ANSYS to evaluate AI‐generated code or simulation workflows. Why Join Us Work on genuinely cutting‐edge AI projects alongside world‐class research teams.

Fully remote and flexible — work when and how much you want, within a 10–40 hour/week range. Gain rare, behind‐the‐scenes exposure to how advanced large language models (LLMs) are trained and evaluated. Freelance autonomy with the intellectual depth of high‐stakes engineering work.

Potential for ongoing contract extension as projects evolve. #J-18808-Ljbffr

Apply