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Freelance Machine Learning Data Annotation Jobs in Maryland

GRVTY

Data Scientist 2

Annapolis Junction, MD · On-site

We have varying levels of Data Scientist roles, depending on years of experience and education ... This role combines artificial intelligence and machine learning skills with a strong foundation in ...

Independent Software

$110 - $150/hr

Depending on the program, you may work with machine learning, artificial intelligence, predictive analytics, data visualization, workflow automation, or other advanced analytical techniques. This ...

EOA Technologies LLC

Job Type Full-time Description EOA Technologies is seeking a Data Scientist to develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets.

Lynker Corporation

Machine Learning Engineer

College Park, MD · On-site

$120 - $180/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Machine Learning Engineer will perform their job duties to a high standard, working both ... Conduct a comprehensive review of state-of-the-art AI-based data assimilation and end-to-end ...

GRVTY

Data Scientist 3

Annapolis Junction, MD · On-site

Bachelor'sDegree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

Lynker Corporation

Machine Learning Engineer

College Park, MD

$95K - $195K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Machine Learning Engineer will perform their job duties to a high standard, working both ... Conduct a comprehensive review of state-of-the-art AI-based data assimilation and end-to-end ...

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Freelance Machine Learning Data Annotation information

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Maryland?

The most popular types of Machine Learning Data Annotation jobs in Maryland are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Maryland?

For Freelance Machine Learning Data Annotation jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Maryland look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Maryland are:

What cities in Maryland are hiring for Freelance Machine Learning Data Annotation jobs?

Cities in Maryland with the most Freelance Machine Learning Data Annotation job openings:

Freelance Machine Learning Data Annotation jobs near you

Data Scientist 2

GRVTY

Annapolis Junction, MD • On-site

Full-time

Re-posted 3 days ago

Job description

What Impact You'll Have

  • We are actively searching for Data Scientists, located in Maryland, to support our team. We have varying levels of Data Scientist roles, depending on years of experience and education.
  • The ideal candidate should possess expertise in AI/ML, proficiency in Python, and hands-on experience with deep learning frameworks such as PyTorch and TensorFlow, with an added advantage if they have cyber knowledge. This role combines artificial intelligence and machine learning skills with a strong foundation in programming and cybersecurity.

What You'll be Owning

  • Foundations: (Mathematical, Computational, Statistical) 2. Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility)
  • Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)
  • Devise strategies for extracting meaning and value from large datasets.
  • Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
  • Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in NSA/CSS data holdings.
  • Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
  • Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting NSA/CSS collection, processing, storage and analytic capabilities and limitations.

What You Must Have

  • Bachelor's Degree with 3 years of relevant experience or an Associates degree with 5 years of relevant experience  
  • Bachelor'sDegree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning)  and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence).  College-level requirements, or upper-level math courses designated as elementary or basic do not count.  Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.
  • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python)), statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g., data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred. 
  • Active TS/SCI with a polygraph 

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