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Machine Learning Intern Jobs in Edison, NJ (NOW HIRING)

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Machine Learning Intern information

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$26.4K

$44.1K

$91.1K

How much do machine learning intern jobs pay per year?

As of Aug 5, 2026, the average yearly pay for machine learning intern in Edison, NJ is $44,085.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,600.00 and $47,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning intern, and why are they important?

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

More about Machine Learning Intern jobs
What are the most commonly searched types of Machine Learning jobs in Edison, NJ? The most popular types of Machine Learning jobs in Edison, NJ are:
What job categories do people searching Machine Learning Intern jobs in Edison, NJ look for? The top searched job categories for Machine Learning Intern jobs in Edison, NJ are:
What cities near Edison, NJ are hiring for Machine Learning Intern jobs? Cities near Edison, NJ with the most Machine Learning Intern job openings:
Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Edison, NJ as of July 2026, with employment types broken down into 10% Internship, 1% As Needed, 56% Full Time, 28% Part Time, 2% Temporary, and 3% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $44,085 per year, or $21.2 per hour.

Machine Learning Engineer, Next-Generation Recommendation Systems

Unity

Manhattan, NY • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
Unity's Vector AI team builds machine learning systems for ad targeting across billions of users. They are seeking a Machine Learning Engineer to develop next-generation recommendation systems that leverage advanced techniques such as reinforcement learning and large language models.
Responsibilities:
• Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
• Develop user understanding systems — conversion prediction, behavioral modeling, and value estimation — that operate across billions of impressions.
• Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
• Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
• Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
• Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.
Qualifications:
Required:
• PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
• Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
• Experience working with large-scale data and ML systems, whether through research or industry internships.
• Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• A track record of rigorous, high-quality research — publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
• Strong written and verbal communication skills — able to make complex ideas accessible across technical and non-technical audiences.
Preferred:
• Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
• Hands-on experience with production ML pipelines — training at scale, feature engineering, or experimentation infrastructure.
• Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
• Familiarity with agentic AI approaches — multi-step reasoning, tool use, or human-AI collaboration frameworks.
• Exposure to causal inference, uplift modeling, or A/B testing at scale.
• Genuine curiosity about applied research and the drive to see ideas through to impact.
Company:
Unity [NYSE: U] offers a suite of tools to create, market, and grow games and interactive experiences across all major platforms from mobile, PC, and console, to extended reality. Founded in 2004, the company is headquartered in San Francisco, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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