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Deep Learning Engineer Intern Jobs in Ridgewood, NJ

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models * Strong software engineering ability to build and maintain complex systems and work with large ...

Showing results 21-40

Deep Learning Engineer Intern information

See Ridgewood, NJ salary details

$8

$17

$24

How much do deep learning engineer intern jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for deep learning engineer intern in Ridgewood, NJ is $17.24, according to ZipRecruiter salary data. Most workers in this role earn between $14.62 and $19.47 per hour, depending on experience, location, and employer.

What is the difference between Deep Learning Engineer Intern vs Machine Learning Engineer Intern?

AspectDeep Learning Engineer InternMachine Learning Engineer Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; familiarity with deep learning frameworksSimilar educational background; knowledge of machine learning algorithms and programming skills
Work EnvironmentResearch labs, tech companies, startups focusing on neural networks and AI modelsBroader industry settings including finance, healthcare, and tech, working on various ML models
Employer & Industry UsageUsed in companies developing AI products, autonomous systems, and advanced neural network applicationsApplied across industries for predictive analytics, data modeling, and automation tasks

While both roles involve machine learning concepts, a Deep Learning Engineer Intern specializes in neural networks and deep learning frameworks, whereas a Machine Learning Engineer Intern works on a wider range of algorithms and models across various industries.

What cities near Ridgewood, NJ are hiring for Deep Learning Engineer Intern jobs?

Cities near Ridgewood, NJ with the most Deep Learning Engineer Intern job openings:

Machine Learning Engineer

Pivotal Solutions

Manhattan, NY • On-site

Full-time

Medical, Dental, Vision

Re-posted 18 days ago


Job description


Job Overview:
We are seeking a skilled Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying machine learning models to solve real-world problems. You will work closely with data scientists, software engineers, and business stakeholders to implement advanced machine learning solutions and drive innovation within the company.
Key Responsibilities:
  • Design and develop scalable machine learning models and algorithms.
  • Collaborate with cross-functional teams to integrate machine learning models into production systems.
  • Analyze large datasets to extract actionable insights and identify patterns.
  • Tune and optimize machine learning models for performance and accuracy.
  • Stay current with the latest advancements in AI and machine learning technologies.
  • Work with software development teams to ensure models are deployed efficiently and effectively.
  • Develop and maintain documentation for models, algorithms, and tools used.

Requirements
  • Bachelor's or Master's degree in Computer Science, Mathematics, or related field.
  • Proven experience in machine learning, data science, and AI technologies.
  • Proficiency in Python, R, or other programming languages used in machine learning.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Strong understanding of data structures, algorithms, and statistical modeling.
  • Familiarity with cloud platforms (AWS, GCP, Azure) for deploying machine learning models.
  • Excellent problem-solving skills and the ability to work independently or in a team.
  • Strong communication skills to explain technical concepts to non-technical stakeholders.

Preferred:
  • Experience with deep learning techniques and natural language processing (NLP).
  • Prior experience in deploying machine learning models in a production environment.
  • Familiarity with DevOps practices and tools for machine learning pipelines (e.g., Docker, Kubernetes).

Benefits:
  • Competitive salary and performance bonuses.
  • Health, dental, and vision insurance.
  • Flexible working hours and remote work options.
  • Professional development opportunities.