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Freelance Machine Learning Data Annotation Jobs in Texas

Apple

Senior Manager - AI Data Operations

Austin, TX

... machine learning and analytics solutions. You'll partner across technical and program teams to ... Description You will lead an organization of internal domain experts, building scalable annotation ...

PROS Holdings, Inc.

Machine Learning Engineer II

Houston, TX · On-site

$93K - $127K/yr

Design, implement, and productionize machine learning models and data pipelines in collaboration with data scientists and engineers. * Design, implement, and productionize machine learning models and ...

PROS

Machine Learning Engineer II

Houston, TX

$93K - $127K/yr

Design, implement, and productionize machine learning models and data pipelines in collaboration with data scientists and engineers. * Design, implement, and productionize machine learning models and ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

1872 Consulting

Machine Learning Engineer

Austin, TX

They enable their customers to extract actionable insight from their data at the point of collection and indefinitely in the future with the help of AI/Machine Learning. The product they offer allows ...

Shipwell

Machine Learning Engineer

Austin, TX · On-site +1

About the Role As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building ... You'll design, develop, and maintain the data pipelines and ML infrastructure that power our ...

Avride

Machine Learning Engineer

Austin, TX

Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

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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:
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Texas? For Freelance Machine Learning Data Annotation jobs in Texas, the most frequently searched job titles are:
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Freelance Machine Learning Data Annotation jobs near you
Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Machine Learning Engineer, (Applied Machine Learning), AI & Data Platforms (AiDP)

Apple

Austin, TX • On-site

$139K - $258K/yr

Full-time

Medical, Dental, Retirement

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

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

Imagine what you could do here. At Apple, revolutionary ideas have a way of becoming extraordinary products, services, and customer experiences. Join the Ai Data Platform Applied Machine Learning team to pioneer enterprise solutions where generative AI meets Apple's unique commitment to privacy-first innovation. Together, we'll create tools that redefine industries while safeguarding what matters most - our users' trust.
Description
As a pivotal member of Apple's enterprise generative AI efforts, you will help design, build, and evolve models, tools and applications that power high-impact AI experiences across the company. You will contribute to the architecture and optimization of AI/gen AI systems built for high availability, scalability, and reliability, working across backend services and application layers. You would solve AI problems in gen AI Safety, machine translation, content understanding, multi-modality, multi-agent systems, fine tuning and more. Our team designs and implements SOTA AI Models, services, and AI platform components that advance adoption of gen AI at apple. We tackle unique AI challenges in AI Safety, privacy-preserving generations, efficient inference, and multimodal integration, while enabling teams to build on top of our foundations. We deliver production-grade systems and models that meet Apple's rigorous standards for quality, performance, and scalability.
Preferred Qualifications
MS or Phd in Machine Learning, Natural Language Processing, Computer Vision or related areas strongly preferred
Experience in ML frameworks for training, fine-tuning, and deploying ML/generative models at scale
Proven track record of building large scale, enterprise-grade ML/Gen-AI products in cloud environments (AWS, GCP , Azure) or on-prem infrastructure
Minimum Qualifications
Bachelor of Science in Computer Science, Machine Learning, or a related quantitative field or equivalent experience
2+ years of hands-on experience in applied AI/machine learning work in industry or 4+ years of hands on AI research and development experience in academia
Demonstrated expertise in generative AI, computer vision, natural language processing, or general machine learning with a passion for problem solving.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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Benefits

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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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