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Scientific Machine Learning Jobs in New Jersey (NOW HIRING)

Harrison Finch

Machine Learning Engineer

Edgewater, NJ

  • Medical

  • Dental

  • Vision

  • Life

Bachelor's in Computer Science, Machine Learning, or related technical field. * 3+ years of experience developing and deploying deep generative models. * Solid experience in pre-training models and ...

Varsity Tutors

Machine Learning Tutor

Point Pleasant, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Elizabeth, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Jersey City, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Paterson, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Paramus, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

New Brunswick, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Westfield, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Clifton, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Trenton, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Hoboken, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Summit, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

You'll work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models. What you'd be doing:

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Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in New Jersey?

For Scientific Machine Learning jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in New Jersey look for?

The top searched job categories for Scientific Machine Learning jobs in New Jersey are:

What cities in New Jersey are hiring for Scientific Machine Learning jobs?

Cities in New Jersey with the most Scientific Machine Learning job openings:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Engineer

Harrison Finch

Edgewater, NJ

Full-time

Medical, Dental, Vision, Life

Re-posted 27 days ago

Job description

The Role
We are building the first generation of biological reasoning models—generative AI systems that can decode biology across scales, from molecules to whole organisms. The goal is to predict, understand, and program living systems in ways never before possible.

As a Machine Learning Engineer, you will design and scale deep generative models for biology. You’ll collaborate closely with experienced founders and domain experts to push the boundaries of how AI can be applied in life sciences.

What You’ll Do

  • Build foundational models that can “read and write” biology at scale.
  • Develop and experiment with generative architectures (transformers, diffusion, autoencoders) to capture complex, multi-scale biological data.
  • Work on distributed training pipelines handling billions of parameters across multi-GPU and multi-node environments.
  • Engineer efficient data pipelines for massive datasets, optimizing for speed, memory, and reproducibility.
  • Design robust evaluation frameworks to ensure integrity, prevent leakage, and validate models against real-world biological problems.

What We’re Looking Fo
  • Bachelor’s in Computer Science, Machine Learning, or related technical field.
  • 3+ years of experience developing and deploying deep generative models.
  • Solid experience in pre-training models and distributed computing environments.
  • Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, JAX).
  • Familiarity with large-scale datasets and scaling models to billions of parameters.
  • Strong grasp of ML fundamentals: architectures, optimization, and evaluation.
  • Experience designing and managing large-scale data pipelines.
  • Background in robust evaluation methods for complex ML projects.
  • Strong coding practices: version control, testing, collaborative workflows.

Who You Are

  1. Problem-solver who thrives in ambiguity and takes ownership.
  2. Clear communicator who can explain complex technical ideas.
  3. Motivated to make a real-world impact through AI in life sciences.
  4. Pragmatic and focused, but curious enough to test unconventional ideas.

Bonus Points

  • Experience applying ML to biology or chemistry.
  • Publications or open-source contributions in ML/AI.
  • High-performance computing and ML Ops experience.

Culture & Values
❤️ Ownership and pride in your work.
???? Commitment to excellence and high standards.
???? Practical, results-oriented mindset.
???? Honest and transparent communication.
???? Belief that work should also be fun and rewarding.

What’s Offered

  • Competitive salary and meaningful equity.
  • Medical, dental, and vision coverage.
  • A culture of feedback and growth: leadership sets high expectations, shares constructive input, and welcomes ideas from every team member.
  • Freedom to manage your day-to-day while hitting key milestones.
  • A chance to shape the culture and direction of the team from an early stage.