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New Grad Robotics Engineer Jobs in New Brunswick, NJ

Maximor AI

Software Engineer (New Grad)

New York, NY · On-site

... New grad" is how you start here. It isn't a track, and it isn't a ceiling. Problems Worth Your ... Context engineering over transactions, ledgers, contracts, policies, and historical decisions ...

Confido

New Grad Software Engineer

New York, NY · On-site

$170K/yr

The Role As a Full-Stack Engineer (Early Career) at Confido, you will help build new product features and systems from the ground up. You'll work closely with experienced engineers to develop AI ...

Whatnot

Software Engineer, 2027 New Grad

New York, NY · On-site

$155K - $160K/yr

The people here are shaping how an entirely new industry develops. As a remote co-located team, w ... The engineering team operates with a high level of autonomy so we need to hire people we can trust.

New

Skanska USA

New Grad Estimating Engineer

Carteret, NJ · On-site

$78K/yr

Bachelor's Degree - Engineering, Construction Management or similar technical training/experience ... S. operates 28 offices across the country, with its headquarters in New York City. In 2024, the U.S ...

Skanska USA

New Grad Estimating Engineer

Carteret, NJ · On-site

$98K/yr

Bachelor's Degree - Engineering, Construction Management or similar technical training/experience ... S. operates 28 offices across the country, with its headquarters in New York City. In 2024, the U.S ...

N1

New Grad Software Engineer (Backend Rust)

New York, NY · On-site +1

$120K - $260K/yr

As a key member of the software engineering team, you will spearhead the development of the core ... The range displayed on each job posting reflects the minimum and typical maximum target for new ...

N1

New Grad Software Engineer (Full Stack)

New York, NY · On-site

$100K - $180K/yr

We are seeking a Software Engineer, Full-Stack to join our engineering team full-time. This role ... The range displayed on each job posting reflects the minimum and typical maximum target for new ...

Uncountable

Product Manager (New Grad)

New York, NY · On-site

$125K - $140K/yr

Thank you for your interest in Uncountable Engineering! Description Uncountable is looking for a ... This role is an in-person role working out of either our San Francisco or New York office. Primary ...

Flexport

Area Manager - New Grad

Newark, NJ

... Engineering teams. You Should Have * A bachelor's degree completed within the last 12 months, or ... Strong problem-solving skills and comfort learning new processes quickly in a fast-paced, sometimes ...

New

Maximor AI

Startup Generalist (New Grad)

New York, NY · On-site

The accountant + engineer loop is the moat. The people who sit with controllers and build from what ... In-person in New York City. Five days a week, in the same room as the founders. That's the point of ...

Aescape Inc

Robotics Test Engineer

New York, NY · On-site

Aescape is a New York-based physical AI and robotics company redefining human recovery through ... Aescape is looking for a Robotics Test Engineer to be the technical conscience of Aescape ...

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Showing results 21-40

All JobsNew Grad Robotics Engineer JobsNew Grad Robotics Engineer Jobs in New Brunswick, NJ

New Grad Robotics Engineer information

See New Brunswick, NJ salary details

$29.9K

$109K

$174.4K

How much do new grad robotics engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for new grad robotics engineer in New Brunswick, NJ is $108,979.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,200.00 and $131,100.00 per year, depending on experience, location, and employer.

What does a new grad robotics engineer do?

A New Grad Robotics Engineer typically supports the design, development, and testing of robotic systems and automation solutions. They work alongside experienced engineers to write code, integrate sensors and actuators, troubleshoot issues, and help improve the performance of robots. These engineers may also assist in prototyping, data analysis, and documentation. The role provides hands-on experience with robotics hardware and software, making it an important entry point for a career in automation and robotics.

What types of projects and responsibilities can a new grad robotics engineer expect in their first year?

As a new grad robotics engineer, you can expect to work on a variety of tasks such as assisting with the design, development, and testing of robotic systems or subsystems. Typical responsibilities may include writing and debugging code for robot control, collaborating with cross-functional teams like mechanical and electrical engineers, and participating in troubleshooting or integration activities. You may also be assigned to support ongoing research, help document technical processes, and contribute to continuous improvement initiatives. This hands-on experience helps build a strong foundation and often opens up future opportunities for specialization or advancement.

What are the key skills and qualifications needed to thrive as a new grad robotics engineer, and why are they important?

To thrive as a New Grad Robotics Engineer, you typically need a degree in robotics, mechanical engineering, computer science, or a related field, along with a solid understanding of control systems, kinematics, and programming languages such as Python or C++. Familiarity with robotics development platforms (like ROS), CAD software, and hands-on experience with sensors and actuators are highly valuable. Strong problem-solving abilities, teamwork, and effective communication skills help you adapt to complex projects and collaborate across disciplines. These competencies ensure you can design, build, and troubleshoot robotic systems efficiently in a fast-evolving technological environment.

What is the difference between New Grad Robotics Engineer vs Robotics Software Engineer?

AspectNew Grad Robotics EngineerRobotics Software Engineer
Required CredentialsBachelor's degree in robotics, mechanical, electrical engineering, or related fieldBachelor's or master's in computer science, robotics, or related field; programming skills essential
Work EnvironmentEntry-level, team-based projects in research labs or tech companiesDeveloping and maintaining robotics software in industry or research settings
Employer & Industry UsageStartups, research institutions, tech companies focusing on roboticsTech firms, industrial automation, autonomous vehicle companies

The main difference is that New Grad Robotics Engineers focus on gaining hands-on experience in robotics projects, often with a broader scope including hardware integration. Robotics Software Engineers primarily concentrate on developing and optimizing software solutions for robotics systems, requiring strong programming skills. Both roles are entry-level but differ in their focus areas within the robotics industry.

What job categories do people searching New Grad Robotics Engineer jobs in New Brunswick, NJ look for?

The top searched job categories for New Grad Robotics Engineer jobs in New Brunswick, NJ are:

What cities near New Brunswick, NJ are hiring for New Grad Robotics Engineer jobs?

Cities near New Brunswick, NJ with the most New Grad Robotics Engineer job openings:

New Grad Robotics Engineer jobs near you
Infographic showing various New Grad Robotics Engineer job openings in New Brunswick, NJ as of August 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $108,979 per year, or $52.4 per hour.

Software Engineer (New Grad)

Maximor AI

New York, NY • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 8 days ago

Key responsibilities

  • Own the development of AI agents that connect to and automate finance systems such as ERPs, banks, billing, payroll, CRM, contracts, spreadsheets, email, and Slack.

  • Build and improve systems for verifying, guardrails, observability, and evaluation of non-deterministic AI to ensure trustworthiness in finance workflows.

  • Ingest, normalize, and reconcile data from various enterprise systems to create a unified source of financial truth.

Job description

About Maximor
Most AI companies are building copilots.
Maximor is building the AI operating system for the CFO office. Our Audit-Ready AI Agents connect to a company's existing finance stack-ERPs, banks, billing, payroll, CRM, contracts, spreadsheets, email, and Slack-and automate the work behind the entire order-to-cash process, record-to-report process, treasury management, financial reporting, and audit readiness.
The goal isn't to help the finance team write better prompts.
The goal is for finance teams to review exceptions while AI does the rest.
What makes Maximor different is our Unified Finance Context-a financial understanding layer that captures transactions, policies, contracts, historical decisions, and accounting judgment. On top of it sit Audit-Ready AI Agents that can reason, explain their decisions, escalate uncertainty, and continuously improve.
We've raised $9M led by Foundation Capital, alongside BoldCap, Gaia Ventures, Aravind Srinivas (CEO of Perplexity), and finance leaders from Zuora, Ramp, Gusto, MongoDB, Zoom, and the Big Four.
What You'll Own
You won't get a starter ticket and a six-month ramp plan.
You'll join a pod of 2-3 engineers that owns a finance domain end-to-end-revenue, cash, close, reporting, payroll, fixed assets, tax, or controls-and you'll own real surface area inside it from your first month: context, prompts, tools, evals, guardrails, and the product around them. A senior engineer pairs with you closely at the start. The bar is that you're scoping and shipping your own work by the end of your first quarter.
No PM writes your specs. No architecture committee approves your ideas. You'll sit with the controllers, accountants, and CFOs who do the work today, understand it properly, then build the agent system that replaces it.
"New grad" is how you start here. It isn't a track, and it isn't a ceiling.
Problems Worth Your Brain
  • How do you build AI agents that finance teams and auditors can trust? Verification, guardrails, observability, and evaluation systems for non-deterministic AI.
  • How do you give an agent the right financial context? Context engineering over transactions, ledgers, contracts, policies, and historical decisions-without bloat, drift, or data leakage.
  • How do you turn messy enterprise systems into a unified source of truth? Ingest, normalize, and reconcile data from ERPs, banks, payroll, billing platforms, CRMs, and email.
  • How do you build agents that get better over time? Systems that explain their reasoning, escalate uncertainty instead of guessing, and improve measurably from human corrections.
  • How do you orchestrate durable AI workflows in the real world? Long-running, replay-safe workflows across flaky, stateful enterprise systems.
  • How do you safely write back to systems of record? Idempotent, audit-ready updates to ERPs and financial systems with full traceability.
A Few Strong Opinions
  • The engineer who can't operate AI agents fluently is becoming obsolete, fast. Fluency with Claude Code, Cursor, and internal agent tooling is a second cortex. Come knowing how to use them; leave knowing how to build with them.
  • "Backend vs. frontend" is dissolving. The agents do the typing. The constraint is product judgment, system design, and the ability to close the loop from problem to shipped feature. Our engineers ship full-stack when the work calls for it.
  • The pod is the unit of leverage. Two engineers who can hold an entire module in their heads ship more than ten engineers who each own a slice. Specialization across pods, generalist within them.
  • The accountant + engineer loop is the moat. Engineers who sit with controllers and build from what they see compound faster than the ones who don't. That starts on day one, not after you've "earned" customer access.
  • We hire for slope as much as intercept-but the intercept still has to clear the bar. We care how fast you learn. We also care that you've already built things that were hard.

What Great Looks Like Here
  • You learn fast and ship faster. You can pick up an unfamiliar codebase or an unfamiliar domain and be productive in days, not weeks. The ability to understand a finance workflow and translate it into software is the single most important skill on this team.
  • You think like an owner. You're a current or future founder who scopes your own work, thinks from the customer's perspective, owns decisions, and drives outcomes without waiting for direction.
  • You solve problems end to end. The team is split vertically. Every engineer makes decisions across the LLM pipeline, infrastructure, backend, and UX.
  • You care about getting it right. A 100% solution beats an 80% one. When something breaks, you dig until you understand why-not just until it stops erroring.
  • You operate AI at two levels. You use coding agents fluently to ship faster, and you have real craft in building the agents that are the product: prompt and context design, tool use, evals, and knowing when a model is the right tool and when plain code is.
  • You communicate clearly. You ask good questions, share progress without being asked, and say "I'm stuck" early instead of late.

What You Should Have Done Before
  • Finishing a bachelor's or master's degree, or graduated within the past year. Computer science, machine learning, or AI strongly preferred; adjacent quantitative degrees welcome if the work backs it up.
  • At least one substantial software engineering or AI engineering internship. Early-stage and AI-native startups count for more here-if you've shipped to production at a company under 50 people, tell us about it.
  • Hands-on experience building with AI agents. Internship, research, coursework, or a serious side project all count. We care that you've actually built one, watched it fail in an interesting way, and can explain what you changed.
  • Real fluency with coding agents. Claude Code, Cursor, or equivalent. You have opinions about which to reach for and when, and you've shipped production code through them.
  • Strong fundamentals in a modern language. Our stack is Python. If your depth is in C++, Java, Go, or Rust, strong fundamentals matter more-be ready to ramp fast.
  • Something real you can walk us through in depth. A side project, a research prototype, an open-source contribution, a hackathon build. We'll go deep on it, so pick something you actually understand.

You'll Stand Out If
  • You've done research in AI, ML, or systems-published or in progress at NeurIPS, ICML, ICLR, ACL, or similar. We weight real-world impact over citation count.
  • You've TA'd or course-assisted a serious systems, ML, or compilers course. Teaching a hard thing well is a strong signal.
  • You've shipped a side project that real people actually used-not just starred.
  • You've contributed to open source that other people depend on.
  • You've built evals, verification, or observability for something non-deterministic and watched it catch a bug before a human did.
  • You've interned at a pre-seed through Series B startup and thrived in the ambiguity.
  • You've done well in competitive programming or olympiads-ICPC, IMO, IPhO, Putnam, or similar.
  • You're curious about fintech, accounting, or how money actually moves.
The Upside
  • Exceptional teammates with high ownership and direct access to customers, CFOs, controllers, and founders.
  • Competitive pay and meaningful early-stage equity.
  • Full medical, dental, and vision coverage for employees and dependents, plus 401(k) match.
  • Meals, a stocked NYC office, and the chance to help define an entirely new category: Audit-Ready AI for Finance.

The Details
  • In-person in New York City. We build in the same room, on purpose.
  • Visa status isn't a filter here. We support OPT and we go the distance on longer-term status for the engineers we hire. The paperwork is our problem, not yours.

Apply