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Freelance Machine Learning Data Annotation Jobs in Texas

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We're hiring ...

Compunnel

Machine Learning Engineer

Plano, TX · On-site

This role will focus on building ML-ready data architectures, developing scalable machine learning solutions, and supporting enterprise analytics initiatives. The ideal candidate will possess hands ...

Gormat

Data Scientist 3

San Antonio, TX · On-site

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

Gormat

Data Scientist 3

San Antonio, TX · On-site

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

Gormat

Data Scientist 3

San Antonio, TX · On-site

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

TalentPros.AI

Staff Machine Learning Engineer

Austin, TX

$120K - $550K/yr

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they ...

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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, and why are they important?

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 Texas? The most popular types of Machine Learning Data Annotation jobs in Texas are:
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Freelance Machine Learning Data Annotation jobs near you
Machine Learning Engineer - Strategic Data Solutions

Machine Learning Engineer - Strategic Data Solutions

Apple

Austin, TX

$113K - $136K/yr

Full-time

Posted yesterday

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Do you love the challenge of solving complex problems that can have a direct and meaningful impact on the company? Do you want to be part of a supportive team that’s constantly learning and having fun while solving tough business problems? We’d love to talk to you if you do!
At Apple, new ideas have a way of quickly becoming outstanding products, services, and customer experiences. Bring passion and dedication to your career, and there's no telling what you could accomplish! Strategic Data Solutions empowers internal partners and optimizes the customer experience by delivering data-driven solutions that mitigate fraud, improve security, and optimize efficiency. Our work touches all parts of Apple, from manufacturing to fulfillment to apps and services. The enormous scale and complexity of the problems and our data present exciting opportunities for pushing the limits of existing data science methods.
As a SDS Machine Learning Engineer, you will work with teams across Apple, using data analysis and predictive modeling techniques to define, build, deploy, and maintain end-to-end operational solutions that have a direct and measurable impact to the company and our customers.
Our commitment to you: We will provide challenging problems that will engage your curiosity. We will provide an organizational culture that values collaboration, problem-solving, and work-life balance. We will provide mentorship to further develop your technical and leadership skills.
Description
• Engage with stakeholders to translate ambiguous business problems into technical solutions, including finding opportunities, breaking them into solvable segments, defining requirements, assessing level of effort, etc
• Work cooperatively to design data science-driven solutions, balancing the utility of tried-and-true techniques and the benefits of custom solutions
• Collaborate with technical partners to implement robust real-time and batch decisioning in production
• Create reporting and monitor decisioning quality to maintain operational and business metric health
• Investigate trends, assess threat impact, and respond with agile logic changes
• Communicate with stakeholders with varying technical backgrounds and business priorities about your work
• Share what you're learning about novel technologies and methods (in data science, machine learning, data engineering, and software engineering, etc) to improve your team's overall technical capabilities
Preferred Qualifications
Theoretical understanding of machine learning algorithms and their relative strengths and weaknesses
Ability to use a querying language such as SQL to extract insights from data
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions
Team-oriented skills and values to facilitate effective collaboration with business and technical partners
Minimum Qualifications
Graduate degree with research/work experience utilizing data science techniques (including but not limited to Computer Science, Statistics, Political Science, Biology, etc) or Bachelor’s degree with equivalent experience
At least 3 years of practical experience (acquired through work, independent projects, or academic research) in deploying machine learning solutions to answer real-world questions
Practical experience with implementing data science-related applications in a programming language such as Python, Scala, or Java

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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