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Machine Learning Data Engineer Jobs in New Jersey

AvePoint is the global leader in data security, governance, and resilience, going beyond ... We are seeking an analytical and innovative Senior Machine Learning Engineer to join our Data & AI ...

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:

Lead, Machine Learning Engineer

Newark, NJ ยท On-site

$107K - $141K/yr

Technology - Data Analytics & Management Are you interested in building capabilities that enable ... As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data ...

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 Engineer

Newark, NJ ยท On-site

$55 - $60/hr

AWS Data Engineer Duties: * Design and build data pipelines and ETL workflows using AWS Glue, AWS ... Familiarity with machine learning pipelines on AWS (SageMaker) * Experience with CI/CD pipelines ...

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Showing results 1-20

Machine Learning Data Engineer information

See New Jersey salary details

$45.2K

$131.7K

$180.2K

How much do machine learning data engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for machine learning data engineer in New Jersey is $131,693.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,200.00 and $139,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Data Engineer position, and why are they important?

To thrive as a Machine Learning Data Engineer, you typically need strong programming skills in Python or Scala, a deep understanding of data structures, algorithms, and machine learning concepts, as well as a degree in computer science or a related field. Experience with big data tools like Spark, Hadoop, and cloud platforms such as AWS or Azure, along with knowledge of data pipelines and ETL processes, is highly valuable; certifications in these areas can be advantageous. Problem-solving ability, attention to detail, and strong communication skills help professionals excel when working with diverse technical teams and stakeholders. These skills ensure data engineers can effectively build reliable, scalable data systems that support the development and deployment of machine learning models.

Can a data engineer become a machine learning engineer?

A data engineer can transition to a machine learning engineer role by gaining knowledge of machine learning algorithms, model development, and deployment techniques. Skills in programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data pipelines are essential for this progression.

What is a Machine Learning Data Engineer job?

A Machine Learning Data Engineer is responsible for designing, building, and maintaining the data infrastructure that supports machine learning models. They develop data pipelines, ensure data quality, and optimize data storage for efficient processing. This role involves working with large-scale datasets, implementing ETL processes, and collaborating with data scientists to deploy machine learning models. Strong knowledge of databases, cloud platforms, and programming languages like Python and SQL is essential. Their work enables organizations to leverage machine learning effectively by providing reliable and scalable data solutions.

Will MLE be replaced by AI?

Machine Learning Data Engineers (MLEs) design, build, and maintain data pipelines and models that AI systems rely on. While AI automation tools can handle some tasks, MLE skills in data engineering, programming, and system architecture remain essential for developing and managing AI infrastructure effectively. The role is expected to evolve with advancements in AI, but it is unlikely to be fully replaced in the near future.

What are the typical daily responsibilities of a Machine Learning Data Engineer?

As a Machine Learning Data Engineer, your daily responsibilities often include designing, building, and maintaining data pipelines that efficiently move and transform data for machine learning applications. You may clean, preprocess, and validate large datasets, optimize storage solutions, and work closely with data scientists to ensure data is accessible and usable for model training and evaluation. Regular collaboration with software engineers and business analysts is common to align project goals and solve data-related challenges. Staying up to date with the latest tools and technologies is also important, as you'll help enable scalable and efficient deployment of machine learning solutions.

What engineers make $500,000?

Senior machine learning data engineers with extensive experience, advanced skills in data architecture, and proficiency in tools like Spark and cloud platforms can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership responsibilities, and industry reputation.

What is a $900000 AI job?

A $900,000 AI-related job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data modeling, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, strategic planning, and may require multiple years of specialized experience or advanced degrees. Compensation at this level reflects the value of expertise in developing and deploying complex AI systems in competitive industries.
What job categories do people searching Machine Learning Data Engineer jobs in New Jersey look for? The top searched job categories for Machine Learning Data Engineer jobs in New Jersey are:
Infographic showing various Machine Learning Data Engineer job openings in New Jersey as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $131,693 per year, or $63.3 per hour.
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

Posted 12 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.