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Product Research Intern Jobs in Ridgewood, NJ (NOW HIRING)

... access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B ... We are looking for PhD research interns with strong research experience in reinforcement learning ...

User Research Intern

New York, NY · On-site

$20 - $32/hr

Support research projects and help synthesize findings for the team * Monitor users' app engagement ... Our team includes designers, engineers, product experts, and finance & operation focused on one ...

Growth Intern

New York, NY · On-site +1

$16.50 - $22/hr

With a focus on enhancing our product offerings, the Growth/Research Intern will also contribute to the development of internal tools that streamline our growth efforts. Requirements: * Undergraduate ...

Hasana, Inc. is committed to developing a fun and productive work culture that is conducive to ... As Market Research Intern for Hasana, Inc. you will have a variety of responsibilities throughout ...

Chaincode Labs is seeking an Research Intern in cryptography, networking, distributed systems ... The organization is well funded and well staffed, with the capacity to produce production-quality ...

Chaincode Labs is seeking an Research Intern in cryptography, networking, distributed systems ... The organization is well funded and well staffed, with the capacity to produce production-quality ...

Showing results 21-40

Product Research Intern information

See Ridgewood, NJ salary details

$9

$21

$38

How much do product research intern jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for product research intern in Ridgewood, NJ is $21.44, according to ZipRecruiter salary data. Most workers in this role earn between $17.50 and $24.33 per hour, depending on experience, location, and employer.

What does a product research intern do?

A Product Research Intern assists in gathering and analyzing data about products, markets, and consumer preferences to help guide the development of new products or improve existing ones. They typically conduct market research, competitor analysis, and user interviews, and may assist in compiling reports for product managers and other stakeholders. This role provides valuable hands-on experience in understanding market trends and user needs, making it an excellent entry point for those interested in product management or market analysis.

What skills and qualifications are needed to thrive as a product research intern?

To thrive as a Product Research Intern, you generally need strong analytical skills, attention to detail, and a background in business, marketing, or a related field. Familiarity with market research tools, survey platforms, and data analysis software like Excel or SPSS is typically required. Effective communication, curiosity, and the ability to collaborate with cross-functional teams are standout soft skills. These competencies are essential for gathering actionable insights, supporting product development, and driving informed business decisions.

What projects and responsibilities can a product research intern expect during their internship?

As a Product Research Intern, you can expect to work on a variety of tasks such as conducting market and competitor analysis, gathering user feedback through surveys and interviews, and assisting in the synthesis of research findings for the product team. Interns often collaborate closely with product managers, designers, and engineers to support data-driven decision making. This role provides hands-on experience in both qualitative and quantitative research methods, and offers valuable exposure to the product development lifecycle within a cross-functional team environment.

What job categories do people searching Product Research Intern jobs in Ridgewood, NJ look for?

The top searched job categories for Product Research Intern jobs in Ridgewood, NJ are:

What cities near Ridgewood, NJ are hiring for Product Research Intern jobs?

Cities near Ridgewood, NJ with the most Product Research Intern job openings:

ML Research Intern

Modal, Inc

New York, NY • On-site

Full-time

Posted 20 days ago


Job description

About Us:
AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable, Ramp, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
Our team includes creators of popular open-source projects (e.g.,Seaborn,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:
We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments.
Preferred Qualifications:
  1. Currently pursuing a PhD in computer science, machine learning, or a related field.
  2. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas.
  3. Experience developing and evaluating large-scale models or machine learning systems.
  4. Familiarity with distributed training, large-scale inference, or multi-GPU environments.
  5. Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR.
  6. Strong programming and engineering skills, with the ability to translate research ideas into working implementations.
  7. A collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.