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Freelance Machine Learning Data Annotation Jobs in Austin, TX

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 ...

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

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

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 ...

The role involves developing and optimizing machine learning models, managing large-scale datasets ... Oversee data collection, preprocessing, and augmentation to maintain high-quality datasets for ...

Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc. Skilled in communication ...

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

This is not a pure data science role. We're looking for an engineer who enjoys building robust ... Machine Learning Engineering ✔ MLOps Engineering ✔ Platform Engineering ✔ Software ...

Experience building data processing pipelines and large scale machine learning systems with ... experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc. Skilled in ...

Experience building data processing pipelines and large scale machine learning systems with ... experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc. Skilled in ...

Big Data Developer

Austin, TX · On-site

$52.50 - $68.25/hr

Experience with machine learning algorithms and automated machine learning to automate and build continuous learning data processing streams and pipelines. Data warehousing tools and techniques, such ...

Experience building data processing pipelines and large scale machine learning systems with ... experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc. Skilled in ...

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

Additionally, real-world data, such as video feeds, can be encoded into neural data to project ... About the Role: Engineers on the BCI team utilize signal processing and machine learning to ...

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Freelance Machine Learning Data Annotation information

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How much do freelance machine learning data annotation jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for freelance machine learning data annotation in Austin, TX is $21.67, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $24.76 per hour, depending on experience, location, and employer.

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 Austin, TX? The most popular types of Machine Learning Data Annotation jobs in Austin, TX are:
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Austin, TX? For Freelance Machine Learning Data Annotation jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Austin, TX look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Austin, TX are:
What cities near Austin, TX are hiring for Freelance Machine Learning Data Annotation jobs? Cities near Austin, TX with the most Freelance Machine Learning Data Annotation job openings:
Infographic showing various Freelance Machine Learning Data Annotation job openings in Austin, TX as of July 2026, with employment types broken down into 2% Locum Tenens, 28% Full Time, 20% Part Time, 16% Contract, 33% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $45,083 per year, or $21.7 per hour.
Machine Learning Engineer - People Analytics

Machine Learning Engineer - People Analytics

Apple

Austin, TX

$184K - $277K/yr

Full-time

Medical, Dental, Retirement

Re-posted 7 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

At Apple, our greatest resource is our people, and the People Analytics Team is dedicated to ensuring Apple’s employees are able to do the best work of their lives.
Our team is looking for a Machine Learning Engineer who is passionate about crafting, implementing, and operating analytical and machine learning solutions that have direct and measurable impact to Apple and its employees.
As a Machine Learning Engineer on Apple's People Analytics Team, you will employ predictive modeling, statistical analysis, and advanced analytical techniques to support solutions for talent management, employee surveys, compensation, and recruiting.
Apple's dedication to privacy, the human-centric nature of our work, and the scale of our business present exciting challenges to traditional machine learning and data science methods. On this team, you will push the limits of existing approaches while delivering tangible business value.
Description
As a Machine Learning Engineer on our team will engage with our business partners to understand their problems, design data-driven solutions, and produce proof-of-concept and prototype solutions. They will collaborate with data engineers and system architects to implement these solutions in a production environment, and be responsible for the ongoing analytic operation of these solution.
","responsibilities":"Design data science / machine learning approaches, applying tried-and-true techniques or developing custom algorithms as needed by the business problem.
Collaborate with data engineers and platform architects to implement real-time and batch decisioning solutions in production.
Ensure operational and business metric health by monitoring production decision points.
Develop metrics to measure performance of analytics solutions, and regularly communicate results to business partners and executives.
Research new technologies and methods across machine learning, data engineering, and data visualization to improve the technical capabilities of the team.
Preferred Qualifications
Ph.D. in I-O Psychology, Economics, Operations Research, Computer Science, or Statistics with a data science fellowship or prior professional experience as a data scientist
Experience working with employee data or HR systems
Minimum Qualifications
MS with 5+ years of professional experience applying data science to real-world business problems
Practical experience with and theoretical understanding of algorithms for classification, regression, clustering, and anomaly detection
Proficiency in writing SQL queries involving database joins and analytical/window functions
Ability to implement data science pipelines, analyses, and applications in a programming language such as Python or R
Prior experience working with employee data or HR systems
Experience with natural language processing (sentiment, topic identification, summarization, entity extraction) and network analysis a plus.
Ability to translate business processes and data into an analytic solution.
Ability to comprehend and debug complex systems integrations spanning multiple toolchains and teams
Ability to extract meaningful business insights from data and identify the stories behind the patterns
Excellent presentation skills, distilling complex analysis and concepts into concise business-focused takeaways
Creativity to engineer novel features and signals, and to push beyond current tools and approaches
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 $184,700 and $277,600, 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.

What Apple employees say

Pay

Benefits

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Workplace

Get the full story on Breakroom


Apple logo

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