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Applied Machine Learning Jobs in New Jersey (NOW HIRING)

From computer vision models that understand what is happening inside an oven to embedded AI systems that make real-time cooking decisions, you will help define how machine learning is applied within ...

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Role purpose Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes ...

Applied AI Researcher

Jersey City, NJ ยท On-site

$104K - $182K/yr

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes that can become ...

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Role purpose Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes ...

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes that can become ...

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Role purpose Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes ...

Applied AI Researcher

Jersey City, NJ ยท On-site

$104K - $182K/yr

Applied AI Researcher GenAI / NLP / Agentic AI / Applied Machine Learning Bridge advanced AI research and practical enterprise use cases by validating models, methods, and prototypes that can become ...

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Applied Machine Learning information

See New Jersey salary details

$25.9K

$43.2K

$89.3K

How much do applied machine learning jobs pay per year?

As of Aug 5, 2026, the average yearly pay for applied machine learning in New Jersey is $43,232.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,000.00 and $46,700.00 per year, depending on experience, location, and employer.

What are the typical collaboration dynamics between applied machine learning engineers and other teams within a company?

Applied Machine Learning engineers often work closely with cross-functional teams including data scientists, software engineers, product managers, and business analysts. They are typically responsible for translating business problems into machine learning solutions and ensuring models are effectively integrated into production systems. This role requires frequent communication to align on project goals, share progress, and address technical challenges, making teamwork and stakeholder management crucial for successful deployments and continuous improvement.

What is applied machine learning?

Applied machine learning involves using machine learning techniques and algorithms to solve real-world problems in various industries, such as healthcare, finance, and technology. Practitioners focus on selecting appropriate models, preparing data, training algorithms, and deploying solutions that deliver tangible value. Unlike theoretical machine learning, applied machine learning emphasizes practical implementation, evaluation, and optimization to meet business or research objectives.

What are the key skills and qualifications needed to thrive as an applied machine learning professional?

To excel in Applied Machine Learning, you need a solid background in mathematics, statistics, computer science, and experience with machine learning algorithms, often supported by a relevant degree or certification. Familiarity with programming languages like Python or R, frameworks such as TensorFlow or PyTorch, and version control systems is typically required. Strong problem-solving abilities, communication skills, and a collaborative mindset help you interpret results and convey insights to diverse stakeholders. These competencies are crucial for building effective models, driving data-driven decisions, and ensuring the successful integration of machine learning solutions into real-world applications.
What are the most commonly searched types of Applied Machine Learning jobs in New Jersey? The most popular types of Applied Machine Learning jobs in New Jersey are:
Infographic showing various Applied Machine Learning job openings in New Jersey as of July 2026, with employment types broken down into 81% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $43,232 per year, or $20.8 per hour.

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

DTCC

Jersey City, NJ โ€ข On-site

$64K - $65K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 14 hours ago


Job description


Are you ready to make an impact at DTCC?
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. We're committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. 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
  • Pension
  • 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).

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: 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.
About Us
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 at www.dtcc.com or connect with us on LinkedIn, X, YouTube, Facebook and 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. 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 by clicking here.
About the Team
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.