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Remote Data Labeling Jobs in Nottingham, MD (NOW HIRING)

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Remote Data Labeling information

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Many remote data labeling jobs are paid per task or project, which can affect overall earnings, and some roles may require basic skills in data annotation tools or image/video labeling software.

How can I make 2000 a week working from home?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the number of tasks completed. To make $2,000 weekly, you would need to consistently complete a high volume of labeled data, often requiring strong attention to detail and familiarity with labeling tools. Achieving this income level may also involve working multiple platforms or combining data labeling with other remote tasks.

How to make $1000 a week remote?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the volume of work completed. To make $1000 weekly, you need to consistently complete a high number of labeled data sets, often requiring strong attention to detail and familiarity with labeling tools. Building a reputation and working with multiple platforms can help increase your income potential.

What are some common challenges faced by remote data labelers, and how can they be managed?

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.

Is data labelling a good career?

Data labeling is a common entry-level role in the AI and machine learning industries, involving annotating data to train algorithms. It offers flexible schedules and requires attention to detail, but typically has lower pay and limited advancement opportunities compared to other tech roles.

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

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

What job categories do people searching Remote Data Labeling jobs in Nottingham, MD look for? The top searched job categories for Remote Data Labeling jobs in Nottingham, MD are:
What cities near Nottingham, MD are hiring for Remote Data Labeling jobs? Cities near Nottingham, MD with the most Remote Data Labeling job openings:
Remote Data Labeling jobs near you
AI Solutions Architect

AI Solutions Architect

Cloudera

Baltimore, MD • Remote

Other

PTO

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

Job description

Business Area:

Professional Services

Seniority Level:

Mid-Senior level

Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world's largest enterprises.

As an AI Solutions Engineer within Cloudera's Public Sector Consulting team, you will be the technical architect and execution lead for agencies moving from "data chaos" to "agentic autonomy." You will work directly with government organizations to design, build, and deploy mission-critical AI applications on the Cloudera Data Platform (CDP).

This is not a "theoretical" role. You will be on the front lines of Phase 2 and Phase 3 adoption journeys-helping customers clean legacy data silos, select the right model architectures, and industrialize MLOps pipelines in highly secure, often air-gapped or hybrid-cloud environments.

As the AI Solutions Engineer you will:

1. AI Model Strategy, Selection and Implementation

  • Evaluate and select optimal model architectures (LLMs, SLMs, or traditional ML) based on mission requirements, considering tradeoffs between accuracy, latency, and cost.

  • Guide customers on "Build vs. Buy vs. Fine-tune" decisions, prioritizing open-source models (Llama, Mistral, Falcon) that can run securely within a sovereign data perimeter.

  • Experience building Agentic Workflows (AI agents that can execute API calls and multi-step tasks).

2. End-to-End Data Engineering

  • Design and implement robust data pipelines within CDP to transform "messy" legacy data into AI-ready formats.

  • Develop and optimize Vector Databases and Retrieval-Augmented Generation (RAG) architectures to ground AI responses in verified agency facts.

  • Build Data pipelines with Spark, Nifi, Kafka or other ETL tools.

3. Optimization & Performance Tuning

  • Optimize model inference for production environments using quantization, pruning, and hardware acceleration (NVIDIA GPU orchestration).

  • Implement LLMOps to monitor model performance, detect hallucination rates, and manage model versioning and drift.

4. Public Sector Advisory & Governance

  • Collaborate with the customer's AI Center of Excellence (CoE) to establish automated guardrails for ethics, bias mitigation, and FedRAMP/IL5 compliance.

  • Translate complex technical AI concepts into mission-value briefings for GS-level stakeholders and agency leadership.

We're excited about you if you have: (Minimum Qualifications):

  • Experience: 5+ years in Data Engineering, Machine Learning, or Software Engineering, with at least 2 years focused on Generative AI or Deep Learning.

  • Technical Stack: Expertise in Python and deep learning frameworks (PyTorch, TensorFlow, Hugging Face).

    • Hands-on experience with Cloudera (CDP), Spark, or similar big data ecosystems.

    • Proficiency in orchestration tools like LangChain, LlamaIndex, or Haystack.

    • Experience developing visual data representations and dashboards (Django, React, or Angular)

    • Experience using a compiled programming language, preferably one that runs on the JVM (Java, Scala, etc)

  • Data Expertise: Proven ability to build ETL/ELT pipelines and work with both SQL and NoSQL/Vector databases (e.g., Pinecone, Milvus, or PGVector).

  • Public Sector Knowledge: Understanding of government security frameworks (NIST AI RMF, FedRAMP, SRGs, STIGs).

  • Active Top Secret Security Clearance

You may also have: (Preferred Qualifications)

  • Experience fine-tuning of foundational models using techniques such as PEFT (Parameter-Efficient Fine-Tuning) and LoRA to adapt AI to domain-specific government nomenclature.

  • Experience training of specialized models on proprietary datasets while ensuring strict adherence to data privacy and sensitivity labels.

  • Experience installing and operating Cloudera Data Platform

  • Experience installing and operating Kubernetes

  • Experience in Air-Gapped deployments and managing AI workloads in disconnected environments.

  • Advanced degree (MS or PhD) in Computer Science, Data Science, or a related field.

  • Active Counterintelligence (CI) or Full Scope (FS) Poly is highly preferred.

This role is not eligible for immigration sponsorship.

What you can expect from us:

  • Generous PTO Policy

  • Support work life balance with Unplugged Days

  • Flexible WFH Policy

  • Mental & Physical Wellness programs

  • Phone and Internet Reimbursement program

  • Access to Continued Career Development

  • Comprehensive Benefits and Competitive Packages

  • Paid Volunteer Time

  • Employee Resource Groups

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