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Full Time Machine Learning Data Annotation Jobs in New Jersey

AvePoint is the global leader in data security, governance, and resilience, going beyond ... Solution Design: Design, build, and deploy machine learning models leveraging structured and ...

Data Scientist

Camden, NJ ยท On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... The target base salary range for this full-time, salaried position is between $109,400-$150,400 ...

Senior Machine Learning Engineer

Jersey City, NJ ยท On-site

$127K - $168K/yr

You'll work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models. What you'd be doing:

Data Scientist

Camden, NJ ยท On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... The target base salary range for this full-time, salaried position is between $109,400-$150,400 ...

Data Scientist

Camden, NJ ยท On-site

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... The target base salary range for this full-time, salaried position is between $109,400-$150,400 ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

New

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

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Showing results 1-20

Full Time Machine Learning Data Annotation information

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 New Jersey? The most popular types of Machine Learning Data Annotation jobs in New Jersey are:
What are popular job titles related to Full Time Machine Learning Data Annotation jobs in New Jersey? For Full Time Machine Learning Data Annotation jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Data Annotation jobs in New Jersey look for? The top searched job categories for Full Time Machine Learning Data Annotation jobs in New Jersey are:
Infographic showing various Full Time Machine Learning Data Annotation job openings in New Jersey as of July 2026, with employment types broken down into 2% Locum Tenens, 27% Full Time, 20% Part Time, 15% Contract, 35% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution.
Associate Director, Principal Data Scientist - Applied AI & Machine Learning Engineering

Associate Director, Principal Data Scientist - Applied AI & Machine Learning Engineering

The Depository Trust Clearing

Jersey City, NJ โ€ข Hybrid

$64K - $65K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 13 days ago


Job description

Are you ready to make an impact at DTCC?ย ย 

Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. ย We're committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact.ย ย We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.

Pay and Benefits:

  • Competitive compensation, including base pay and annual incentive
  • Comprehensive health and life insurance and well-being benefits
  • Pensionย 
  • Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
  • DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee).ย 

The impact you will have in this role:

Being a member of the Technology Research and Innovation team, you will help advance DTCC's ability to explore, validate, and productize emerging data science, machine learning, AI, and GenAI capabilities that create measurable value across the organization. This role sits at the intersection of research, applied machine learning, data engineering, and product development, with a strong focus on moving ideas beyond experimentation into scalable, production-ready solutions. The Principal Data Scientist / Machine Learning Engineer will design and deliver practical, production-oriented solutions in a financial services environment where governance, risk, controls, reliability, and business adoption are critical. This is not a purely theoretical research role; the ideal candidate will have demonstrated experience taking data science, machine learning, AI, or GenAI concepts from ideation through prototype, validation, productization, and deployment while partnering closely with product owners, technology teams, business stakeholders, and innovation leaders to rapidly develop solutions, test feasibility, define a path to production, and align technical work to real business outcomes.

Your Primary Responsibilities:

  • Champion Python-Centric Data Engineering: Spearhead the adoption and optimization of Python for data engineering tasks, including data ingestion, transformation, and advanced analytics. Guide team in leveraging Python libraries and frameworks to build scalable, maintainable solutions
  • Architect Data Pipeline Solutions: Strategically design and implement enterprise-grade data pipelines for optimal data processing thru python and Snowflake. Establish standards for data quality, security, and integrity, and ensure seamless integration of disparate data sources and formats
  • Strategic Cross-Functional Collaboration: Partner with technology teams to identify opportunities for leveraging data and analytics. Translate business requirements into technical solutions and ensure that insights are actionable and aligned with organizational objectives
  • Lead Advanced Machine Learning Initiatives: Direct the design, development, and deployment of robust machine learning models using Python, guiding teams in data preprocessing, feature engineering, model optimization, and evaluation. Oversee the application of advanced techniques, including deep learning, regression, classification, and clustering, to solve high-impact business problems
  • Demonstrate accountability by taking ownership of solution ideation, development, and execution, including coordinating efforts with internal and external teams/stakeholders to present the results (reports and presentations) in a clear and concise manner
  • Technical Leadership and Mentorship: Provide guidance and technical leadership to junior engineers, create high-performance and reusable approaches to solve challenging problems, and cultivate a culture of excellence, continuous learning, and innovation
  • Risk Management and Compliance: Integrate risk and control processes into all data engineering activities, proactively monitor for potential issues, and escalate risks as appropriate to ensure compliance with organizational standards

**NOTE:ย  The Primary Responsibilities of this role are not limited to the details above. **

Qualifications:

  • Minimum 8 years of related experience
  • Bachelor's degree (preferred) or equivalent experience

Talents Needed for Success:

  • Extensive experience in data engineering and machine learning model development using Python
  • Proven expertise in architecting data pipelines with Python and Snowflake
  • Strong leadership and mentorship skills, with experience managing and developing technical teams
  • Excellent communication and collaboration abilities
  • Sound understanding of data governance and risk management
  • Experience in Financial industry is preferred
  • Experience in Data Visualization tools is a plus

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

With over 50 years of experience, DTCC is the premier post-trade market infrastructure for the global financial services industry. From 20 locations around the world, DTCC, through its subsidiaries, automates, centralizes, and standardizes the processing of financial transactions, mitigating risk, increasing transparency, enhancing performance and driving efficiency for thousands of broker/dealers, custodian banks and asset managers. Industry owned and governed, the firm innovates purposefully, simplifying the complexities of clearing, settlement, asset servicing, transaction processing, trade reporting and data services across asset classes, bringing enhanced resilience and soundness to existing financial markets while advancing the digital asset ecosystem. In 2024, DTCC's subsidiaries processed securities transactions valued at U.S. $3.7 quadrillion and its depository subsidiary provided custody and asset servicing for securities issues from over 150 countries and territories valued at U.S. $99 trillion. DTCC's Global Trade Repository service, through locally registered, licensed, or approved trade repositories, processes more than 25 billion messages annually. To learn more, please visit us atย www.dtcc.comย or connect with us onย LinkedIn,ย X,ย YouTube,ย Facebookย andย Instagram.

DTCC proudly supports Flexible Work Arrangements favoring openness and gives people freedom to do their jobs well, by encouraging diverse opinions and emphasizing teamwork.ย ย When you join our team, you'll have an opportunity to make meaningful contributions at a company that is recognized as a thought leader in both the financial services and technology industries. A DTCC career is more than a good way to earn a living. It's the chance to make a difference at a company that's truly one of a kind.

Learn more about Clearance and Settlement byย clicking here.

Serves as a dedicated technology resource for advancing DTCC's business opportunities and providing industry thought leadership for leveraging new technology. The goal of this new department is to partner internally with IT, our business and regulatory divisions and externally with clients, regulators, and fintech vendors, to help build new platforms and business models to advance DTCC's mission to support the financial markets.