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Machine Learning Software Engineer Intern Jobs in Hightstown, NJ

As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and ... machine-learning software systems * Proven experience owning ML systems long enough to see the ...

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

As a Senior Machine Learning Engineer , you will collaborate with data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will ...

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and ... Strong software engineering fundamentals and experience building production systems * Experience ...

Showing results 41-60

Machine Learning Software Engineer Intern information

See Hightstown, NJ salary details

$13

$25

$38

How much do machine learning software engineer intern jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for machine learning software engineer intern in Hightstown, NJ is $25.51, according to ZipRecruiter salary data. Most workers in this role earn between $20.77 and $28.94 per hour, depending on experience, location, and employer.

What does a machine learning software engineer intern do?

A Machine Learning Software Engineer Intern assists in the development, testing, and deployment of machine learning models and algorithms. Their responsibilities typically include data preprocessing, model training, evaluation, and collaborating with senior engineers to integrate machine learning solutions into software products. Interns may also contribute to research, documentation, and code optimization, gaining hands-on experience with real-world machine learning projects. This role provides a valuable opportunity to apply academic knowledge in a professional setting and learn from experienced engineers.

What are the key skills and qualifications needed to thrive as a machine learning software engineer intern?

To thrive as a Machine Learning Software Engineer Intern, you need a solid understanding of programming (especially Python), machine learning algorithms, and data structures, ideally supported by coursework or relevant projects. Familiarity with frameworks such as TensorFlow or PyTorch, experience using version control systems like Git, and knowledge of cloud platforms are highly valuable. Critical thinking, eagerness to learn, and effective communication help interns collaborate with teams and adapt to new challenges. These skills and qualities are crucial for developing robust ML solutions, integrating with production systems, and contributing meaningfully to real-world projects.

What cities near Hightstown, NJ are hiring for Machine Learning Software Engineer Intern jobs?

Cities near Hightstown, NJ with the most Machine Learning Software Engineer Intern job openings:

Quantitative Researcher - Machine Learning

Point72

New York, NY • On-site

Full-time

Re-posted 19 hours ago


Job description

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role/Responsibilities:

We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology.

Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave.  Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation.

Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features.

Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. 

Requirements:

  • PhD or PhD candidate in machine learning, computer science, statistics, or a related field
  • Experience with sequential modeling and time series forecasting using deep learning
  • Experience with deep neural networks and representation learning
  • Prior experience working in a data driven research environment
  • Experience with translating mathematical models and algorithms into code
  • Proficient in programming languages such as Python and R
  • Experience with machine learning software libraries such as TensorFlow or PyTorch
  • Experience with natural language processing technology a strong plus
  • Excellent analytical skills, with strong attention to detail
  • Interest in applying machine learning to finance
  • Collaborative mindset with strong independent research ability
  • Strong written and verbal communication skills

We're looking for exceptional colleagues with unparalleled passion. If you'd like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that you've worked outside of school, or as part of your curriculum. If you're proud of the work you did we want to hear about it. In addition to exceptional statisticians and engineers, we work with talented musicians, writers, mathematicians, and founders of non-profits; we'd love to learn more about what excites you.