2

Full Time Machine Learning Data Annotation Jobs in Austin, TX

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 ...

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 ... Base Salary Range: $199,000-$331,000 USD What We Offer: Full-time employees are eligible for the ...

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 ...

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 ...

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.

... data-driven decisions • Develop scalable machine learning pipelines and systems • Maintain up-to-date knowledge of emerging AI and machine learning trends • Ensure the quality and performance ...

... data-driven decisions Develop scalable machine learning pipelines and systems Maintain up-to-date knowledge of emerging AI and machine learning trends Ensure the quality and performance of AI systems ...

This position is ideal for an experienced Data Science / Machine learning leader who is passionate about collaborating with business and technology partners and engineers to solve challenging ...

This position is ideal for an experienced Data Science / Machine learning leader who is passionate about collaborating with business and technology partners and engineers to solve challenging ...

Analyze and extract key insights from rich stores of customer data * Research and implement ML ... Machine learning (ML) algorithms * Predictive modeling and analysis * Data visualization software ...

next page

Showing results 1-20

Full Time Machine Learning Data Annotation information

See Austin, TX salary details

$37.2K

$121.7K

$194.8K

How much do full time machine learning data annotation jobs pay per year?

As of Jul 4, 2026, the average yearly pay for full time machine learning data annotation in Austin, TX is $121,659.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $134,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Data Annotation Specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What are Full Time Machine Learning Data Annotation jobs?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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 Full Time Machine Learning Data Annotation jobs in Austin, TX? For Full Time Machine Learning Data Annotation jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Austin, TX look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Austin, TX are:
What cities near Austin, TX are hiring for Full Time Machine Learning Data Annotation jobs? Cities near Austin, TX with the most Full Time Machine Learning Data Annotation job openings:
Machine Learning Engineer

Machine Learning Engineer

Shipwell

Austin, TX • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago


Job description

About Shipwell

At Shipwell, we empower supply chain efficiency and service effectiveness at scale. The Shipwell platform includes capabilities previously out of most shippers' technical reach and affordability today. Our solution combines everything shippers need, from transportation management and visibility to procurement, in a comprehensive, easy-to-use platform. It will adapt and scale as market and business demand change, allowing shippers to operate, manage, and optimize the shipping process seamlessly. Industry experts have recognized Shipwell's traction in the market and have differentiated Shipwell as a leader in the logistics industry. Awards include Gartner Magic Quadrant for TMS 2025, 2024, 2023, 2022, 2021, Food Logistics' 2024 Top Software & Technology Providers, and FreightWaves' FreightTech 2022 and 2021 Awards for Innovation and Disruption in Freight Industry. Shipwell was also named the fourth fastest-growing company in North America on the 2021, 2022, and 2023 Deloitte Technology Fast 500 and Forbes 2020 Next Billion-Dollar Startup.

Our Culture

Shipwell is a fast-paced, high-energy start-up that strives to build the future of shipping every day. Diversity of thought and cross-department collaboration is very important to us. We deliver open, honest, careful communication and work as hard as we play. We create & deliver solutions that are revolutionizing the industry, which brings excitement and purpose to our work. If you are looking for a place that will help you tap into your best work-self and give you hands-on experience building something big, then we invite you to come and build the future of shipping with us!

About the Role

As a Machine Learning Engineer at Shipwell, you'll play a pivotal role in building and scaling our AI-powered logistics solutions. You'll design, develop, and maintain the data pipelines and ML infrastructure that power our autonomous digital workers and drive data-driven decision-making across the organization.

Your work will span the full machine learning lifecycle—from extracting and transforming data from diverse sources to implementing production-grade ML models in our cloud environment. You'll optimize our AWS infrastructure, establish data integrity standards, and create scalable architectures that enable research teams to access the data they need. Working closely with engineering, analytics, data science, and product teams, you'll take our machine learning capabilities to the next level.

This is a dynamic opportunity to become the expert on Shipwell's ML and data infrastructure, make critical technical decisions, and contribute to projects at the forefront of GenAI and machine learning in the logistics industry. You'll own the processes you create and have the opportunity to grow your skills while revolutionizing how the supply chain operates.

What we're looking for:

  • Experience designing and implementing ML models and maintaining relevant data in AWS
  • Experience working with DevOps to enable your team access to the tools they need
  • Contributing to every part of the machine learning product lifecycle
  • Proven track record of implementing data engineering best practices in all aspects of the data pipeline, i.e. ETL, data integrity, and monitoring
  • Demonstrable proficiency with Python, dbt, SQL, and modern ML tooling
  • Experience working with large-scale data model refactoring for better performance, interpretability, and maintainability
  • Experience with version control tools (GitHub, GitLab) and Agile methodologies.
  • Experience with agentic tooling and pipelines including LangChain, LangGraph, and LangSmith
  • Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, or demonstrated equivalent quantitative experience.
  • Excellent communication skills to effectively collaborate with different teams within the engineering org
What you'll do when you get here:
  • Collaborate closely with our engineering, analytics, data science, and product teams as we take our machine learning projects and infrastructure to the next level
  • Right at the start you will be contributing to existing ML projects, creating and maintaining the data pipelines they need, and communicate the results to the organization
  • You will own all of the data and ML processes you create
  • You will become the expert on our machine learning and data infrastructure and make critical decisions in our path forward
  • You will have the opportunity to grow your skill set and take part in projects at the forefront of GenAI, ML, and data science in the logistics industry

Why Shipwell:

  • Enjoy working remotely with the added perk of a home office reimbursement
  • Unlimited Paid Time Off (PTO)
  • A robust healthcare package that includes medical, dental & vision benefits, short-term and long-term disability, AD&D coverage, and flexible/health savings accounts
  • 401K program where Shipwell matches up to 4%
  • All employees receive stock options
  • A yearly learning and development budget
  • Subsidized internet, cell phone, fitness, and educational reimbursements
  • Virtual team-building events where fun and connection take center stage
  • Join a vibrant, inclusive workplace shaped by friendly, talented individuals
  • Receive a technology package, including a MacBook Pro
  • Employee Recognition Program to celebrate and incentivize hard work and success!

The Salary Range for this role is between $130-$163K per year with bonus upside. Compensation is based on several factors, including market location, job-related knowledge, skills, and experience.

Shipwell is an equal opportunity employer and welcomes all qualified applicants regardless of race, ethnicity, religion, gender, gender identity, sexual orientation, disability status, protected veteran status, or any other characteristic protected by law. We celebrate diversity and believe that experience comes in different forms. Diversity in our team makes for better problem-solving, more creative thinking, and ultimately, a better product and company culture.

Even more important than your resume is a clear demonstration of impact, dedication, and the ability to thrive in a fast-paced and collaborative environment. Shipwell strives to have an inclusive work environment; so if you are hard-working & good at what you do, then please come as you are. We want you to contribute, grow, & learn at Shipwell.

We are looking forward to adding new perspectives to our team!

Shipwell employees will only ever email you about this position from a @shipwell.com email address.

For more information about Shipwell visit shipwell.com, or connect with us on Twitter @shipwell, LinkedIn, and Facebook.com/Shipwellinc