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Internship Machine Learning R Jobs in New York, NY

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

Forhyre

Machine Learning Engineer

New York, NY

Ability to write robust code in Python, Java and R * Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn) * Excellent communication skills * Ability ...

Point72

Machine Learning Engineer

New York, NY · On-site

Proficiency in programming languages such as Python and R * Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience implementing Agent or Context engineering is ...

Point72

Machine Learning Engineer

New York, NY · On-site

Proficiency in programming languages such as Python and R * Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience implementing Agent or Context engineering is ...

Trading Interview

Machine Learning Engineer

Manhattan, NY · On-site

$55 - $83/hr

Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques. Machine learning is a critical pillar of ...

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Internship Machine Learning R information

See New York, NY salary details

$27.9K

$46.6K

$96.3K

How much do internship machine learning r jobs pay per year?

As of Sep 7, 2026, the average yearly pay for internship machine learning r in New York, NY is $46,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,600.00 and $50,300.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning R vs Data Analyst Intern?

AspectInternship Machine Learning RData Analyst Intern
Required SkillsProficiency in R, basic machine learning concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
Work EnvironmentResearch labs, tech companies, startups focusing on AI/ML projectsBusiness environments, consulting firms, marketing agencies
Industry UsagePrimarily in tech, AI, and data science sectorsAcross various industries including finance, marketing, and healthcare

Internship Machine Learning R focuses on applying R programming to develop machine learning models, often in tech and AI sectors. In contrast, Data Analyst Internships emphasize data visualization, statistical analysis, and reporting across diverse industries. Both roles require data handling skills but differ in their focus on machine learning versus data interpretation.

What are the most commonly searched types of Machine Learning R jobs in New York, NY?

The most popular types of Machine Learning R jobs in New York, NY are:

Internship Machine Learning R jobs near you

Machine Learning

Cantor Fitzgerald Securities

Manhattan, NY • On-site

Full-time

Posted 5 days ago

Job description


Join Cantor Fitzgerald Technology Markets LLC as a Machine Learning Engineer focused on building AI-driven solutions for a high-volume financial services business. You will work closely with product, engineering, and business teams to create, test, and operationalize large language model (LLM) applications, ensuring they meet performance, reliability, and responsible-AI standards.
Responsibilities
  • Design and implement LLM-driven features in production systems.
  • Build and maintain data pipelines for both structured and unstructured data.
  • Write clean, testable Python code and maintain reusable libraries.
  • Develop prompts, tool-calling workflows, and retrieval pipelines.
  • Create evaluation suites, define success metrics, and analyze failures.
  • Diagnose and mitigate hallucination, latency, and cost issues.
  • Collaborate with product, engineering, and business stakeholders.
  • Implement monitoring, logging, and alerting for AI services.
  • Contribute to responsible-AI guardrails and human-in-the-loop processes.
  • Document designs, experiments, and findings for internal knowledge sharing.

Qualifications
  • Bachelor's degree in computer science, machine learning, mathematics, physics, statistics, econometrics, or equivalent practical experience.
  • Experience contributing to production or production-like software through work, internships, research, open source, or substantial personal projects.
  • Strong programming ability in Python with clear, tested, and maintainable code.
  • Experience with web services, data integrations, testing, logging, and basic monitoring across diverse data types.
  • Hands-on experience building with LLM tools or frameworks (prompting, structured outputs, tool-calling, retrieval, multi-step workflows) and awareness of common failure modes.
  • Experience evaluating LLM-powered applications: building test sets, reviewing failures, defining metrics, and iterating on prompts or retrieval.
  • Solid grounding in machine learning, statistics, and experimental design with ability to interpret technical papers and documentation.
  • Strong communication skills and comfort working with product, engineering, and business partners.
  • Interest in applying AI responsibly in financial services, including privacy, security, human review, and appropriate automation.
  • Familiarity with cloud deployment, containers, and modern release pipelines.

$140,000 - $160,000

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