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Internship Edge Ai Machine Learning Jobs in Ridgewood, NJ

This is an opportunity to work at the intersection of machine learning, embedded systems, computer vision, and smart consumer technology, bringing cutting-edge AI from research into products used by ...

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Internship Edge Ai Machine Learning information

See Ridgewood, NJ salary details

$25.8K

$43.1K

$89K

How much do internship edge ai machine learning jobs pay per year?

As of Aug 20, 2026, the average yearly pay for internship edge ai machine learning in Ridgewood, NJ is $43,085.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,900.00 and $46,500.00 per year, depending on experience, location, and employer.

What is an internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.

What are the key skills and qualifications needed to thrive as an internship edge AI machine learning professional, and why are they important?

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

What job categories do people searching Internship Edge Ai Machine Learning jobs in Ridgewood, NJ look for?

The top searched job categories for Internship Edge Ai Machine Learning jobs in Ridgewood, NJ are:

Infographic showing various Internship Edge Ai Machine Learning job openings in Ridgewood, NJ as of June 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 65% Physical, 4% Hybrid, and 31% Remote job distribution, with an average salary of $43,085 per year, or $20.7 per hour.

Generative AI & Machine Learning Engineer

Morgan Stanley

Manhattan, NY • On-site

$148K - $199K/yr

Other

Posted 13 days ago


Morgan Stanley rating

8.4

Company rating: 8.4 out of 10

Based on 155 frontline employees who took The Breakroom Quiz

33rd of 151 rated financial services


Job description

In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Generative AI & Machine Learning Engineering position at the Vice President level, which is part of the job family responsible for developing and maintaining software solutions that support business needs.
Morgan Stanley is an industry leader in financial services, known for mobilizing capital to help governments, corporations, institutions, and individuals around the world achieve their financial goals.
Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on.
Technology works as a strategic partner with Morgan Stanley business units and the world's leading technology companies to redefine how we do business in ever more global, complex, and dynamic financial markets. Morgan Stanley's sizeable investment in technology results in quantitative trading systems, cutting-edge modeling and simulation software, comprehensive risk and security systems, and robust client-relationship capabilities, plus the worldwide infrastructure that forms the backbone of these systems and tools. Our insights, our applications and infrastructure give a competitive edge to clients' businesses-and to our own.
The Team:
The Investment Banking and Global Capital Markets Technology is a globally distributed but close-knit team based in NY, LN, Mumbai, Bengaluru and Pune. We are a highly innovative team that works in small groups that learn, grow, and succeed together. We follow Agile development practices to deliver high quality solutions that delight our customers. As a member of the team, you will interact with others who are genuine and want you to succeed. Your talent, experience, and voice are valued and will make a difference.
We are seeking an experienced and hands-on engineering leader specializing in Generative AI (GenAI), Large Language Models (LLMs), intelligent agents, and Machine Learning. This role is ideal for a technical leader who enjoys solving complex engineering problems, working closely with business and technology partners, and leading the end-to-end delivery of AI-powered products in a fast-paced investment banking environment.
What you'll do in the role:
  • Lead the end-to-end design, development, and delivery of enterprise AI and machine learning solutions from concept through production deployment.
  • Architect scalable, secure, and resilient AI platforms leveraging LLMs, Retrieval-Augmented Generation (RAG), intelligent agents, and modern machine learning techniques.
  • Provide hands-on technical leadership during solution design, implementation, code reviews, and production support.
  • Drive technical decision-making to ensure solutions are scalable, maintainable, and aligned with enterprise engineering standards.
  • Collaborate closely with product owners, business stakeholders, architects, and engineering teams to translate business requirements into high-quality technical solutions.
  • Lead technical planning, estimation, sprint execution, and delivery across multiple concurrent initiatives.
  • Ensure AI solutions are production-ready with appropriate monitoring, observability, testing, security, and operational support.
  • Drive engineering best practices including CI/CD, automated testing, code quality, infrastructure automation, and MLOps.
  • Evaluate emerging AI technologies and recommend practical adoption where they improve delivery or engineering productivity.
  • Mentor engineers and promote engineering excellence through technical guidance, design reviews, and knowledge sharing.

What you'll bring to the role:
  • 10+ years of AI/ML and software engineering experience, with a proven track record of designing, developing, and delivering production-grade AI solutions in enterprise environments.
  • Proven experience leading engineering teams and delivering complex technology initiatives in large enterprise environments.
  • Strong hands-on experience developing production-grade AI and machine learning applications.
  • Deep experience with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, and agent-based architectures.
  • Strong programming skills in Python, with experience in Java or another enterprise programming language preferred.
  • Experience developing distributed systems using microservices, REST APIs, containerization, and cloud-native architectures.
  • Experience deploying AI applications using modern MLOps and DevOps practices.
  • Strong understanding of software engineering fundamentals including system design, scalability, resiliency, testing, and performance optimization.
  • Excellent communication skills with the ability to lead technical discussions across engineering and business teams.
  • Experience working in Agile software development environments.
  • Experience with OpenAI, Azure OpenAI, LangChain, LangGraph, or similar AI frameworks.
  • Experience with vector databases and Retrieval-Augmented Generation (RAG) architectures.
  • Experience building AI copilots, workflow automation, or agentic AI applications.

Preferred Qualifications
  • Experience within Investment Banking, Capital Markets, or Financial Services technology.
  • Experience with Kubernetes, Docker, GitHub Actions, Jenkins, MLflow, or similar DevOps and MLOps tooling.
  • Familiarity with cloud platforms such as Azure, AWS, or Google Cloud

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.
To learn more about our offices across the globe, please copy and paste into your browser.
Expected base pay rates for the role will be between $155,000 and $215,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.
Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.
Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.
For more information, please visit:

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About Morgan Stanley

Sourced by ZipRecruiter

Since our founding in 1935, Morgan Stanley has been committed to serving local and global communities by being a market leader in Investment Banking, Securities, Investment Management and Wealth Management services. Our belief that capital can work to benefit all of society inspires us to put our clients first, lead with exceptional ideas, hold our business to high ethical standards, and give back to communities around the world through philanthropy and public works. We have a smart casual dress code and operate under a philosophy that balances work with your personal life. Our people's talent, passion, and expertise is the fuel on which our organization runs, therefore, our people are our greatest asset. Diversity and inclusiveness is a critical component for our success and it is our priority to continue building a firm that values the unique background and identity of every one of our employees, thus enabling our people to bring their full, and best selves to work each day. Teamwork is the essence of our approach, and so are the values of integrity, excellence, and enabling our people to achieve at the highest levels. We invite you to learn more about our commitment to diversity and serving our community.

Industry

Finance and insurance and software development

Company size

10,000+ Employees

Headquarters location

New York, NY, US