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Full Time Machine Learning Data Annotation Jobs in Seattle, WA

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... Participate in the full development cycle: data collection, labeling, model development ...

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core ... Data Analysis and Insight Generation : Analyze experimental data to extract actionable insights.

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... Maintain awareness of industry best practices for data maintenance handling as it relates to your ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... Maintain awareness of industry best practices for data maintenance handling as it relates to your ...

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

Responsibilities : • Study and transform data science prototypes • Design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning ...

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

Responsibilities : • Develop and maintain the infrastructure to support machine learning workflows for drug discovery at scale. • Implement and optimize algorithms for data processing, model ...

This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing ...

Qualifications : Required : • Bachelor's degree in Computer Science, ML, Data Science, or ... machine learning concepts and workflows • 1-3 years of experience in coding using Python with ...

They are seeking a Machine Learning Engineer to develop AI-powered features that extract insights from structured and unstructured data, focusing on natural language processing and machine learning ...

Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying ... Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical ...

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Full Time Machine Learning Data Annotation information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

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

As of Jun 9, 2026, the average yearly pay for full time machine learning data annotation in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 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 popular job titles related to Full Time Machine Learning Data Annotation jobs in Seattle, WA? For Full Time Machine Learning Data Annotation jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in Seattle, WA look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in Seattle, WA are:
Senior Machine Learning Engineer - E-commerce Merchant and Creator Growth

Senior Machine Learning Engineer - E-commerce Merchant and Creator Growth

TikTok

Seattle, WA • On-site

$202K - $368K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 3 days ago


TikTok rating

7.6

Company rating: 7.6 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

112th of 186 rated software companies


Job description

Responsibilities
Our Team Supply Side Algorithms Our team is committed to expanding the number of merchants and creators on TikTok Shop, as well as providing them with comprehensive support to foster growth within the TikTok Shop ecosystem. We achieve this by developing end-to-end algorithmic capabilities utilizing machine learning, data mining, and causal inference methodologies. We are seeking a talented and motivated Machine Learning Engineer with expertise in marketplace growth to join our dynamic and fast-paced team. In this role, you will collaborate with cross-functional teams including data scientists, product managers, and business stakeholders to develop innovative solutions that drive the growth of merchants and creators in TikTok Shop. Responsibilities 1. Utilize advanced machine learning techniques to analyze large-scale datasets and identify meaningful, correlations, and causal relations related to merchant and creator growth in TikTok Shop 2. Collaborate with business stakeholders, product managers, and data scientists to define data mining objectives and develop strategies to address complex business problems and opportunities. 3. Apply feature engineering techniques to derive relevant features and embeddings from raw data and improve the performance of machine learning models. 4. Develop scalable and efficient data pipelines to preprocess and transform data for machine learning tasks, ensuring data quality, consistency, and availability. 5. Evaluate and benchmark different machine learning approaches, algorithms, and tools, and recommend the most appropriate solutions based on performance, scalability, and interpretability. 6. Stay updated with the latest advancements in data mining, machine learning, and related fields, and apply this knowledge to enhance the team's capabilities and identify new opportunities. 7. Communicate findings, insights, and technical concepts effectively to both technical and non-technical stakeholders, fostering a collaborative and data-driven decision-making culture.
Qualifications
Minimum Qualifications 1. Highly self-motivated to drive business growth and foster technical advancement. 2. Proficient in using SQL and Python and experience with data manipulation 3. Experience with big data processing frameworks (e.g., Hadoop, Spark) and distributed computing for efficient data mining on large-scale datasets. 4. Solid understanding of machine/deep learning concepts and techniques, including feature engineering, model evaluation, and optimization. 5. Strong analytical and problem-solving skills, with a demonstrated ability to handle and derive insights from complex and unstructured datasets. Preferred Qualifications: 1. Master's or advanced degree in Computer Science, Data Science, Statistics, or a related field. 2. 5+ years experience as a Machine Learning Engineer, Data Scientist, and experience in causal machine learning is preferred 3. Work experience in user growth, marketing algorithms, recommendation algorithms, advertisement algorithms or related fields is preferred. 4. Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and convey technical concepts to non-technical stakeholders.
Job Information
[For Pay Transparency]Compensation Description (Annually)
The base salary range for this position in the selected city is $202160 - $368220 annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
For Los Angeles County (unincorporated) Candidates:
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.
About TikTok
TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us
Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect - and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.
We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok Accommodation
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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