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Entry Level Machine Learning Engineer Jobs in New Providence, NJ

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

About the Role We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

You'll work across training infrastructure, inference optimization, and reinforcement learning pipelines in multi-GPU and multi-node environments. Responsibilities: * Performance engineering of ...

Lead, Machine Learning Engineer

Newark, NJ

$107K - $141K/yr

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability ...

Machine Learning Engineer I

New York, NY · On-site

$106K - $146K/yr

CNN is seeking a Machine Learning Engineer I to build and deploy ML systems that power personalization, search, recommendations, and content understanding for millions of users across CNN's digital ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Showing results 21-40

Entry Level Machine Learning Engineer information

See New Providence, NJ salary details

$31.6K

$73K

$124.2K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 11, 2026, the average yearly pay for entry level machine learning engineer in New Providence, NJ is $73,011.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,200.00 and $82,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What cities near New Providence, NJ are hiring for Entry Level Machine Learning Engineer jobs? Cities near New Providence, NJ with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in New Providence, NJ as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $73,011 per year, or $35.1 per hour.

Senior Machine Learning Engineer

exacare ai

New York, NY • On-site

$114K - $157K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 29 days ago


Job description

About the Role
We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows, infrastructure, and processes that enable ML to move from research into reliable production systems.
You will partner closely with research-oriented ML teammates and help turn their work into scalable, maintainable, and cost-effective production systems. This includes building and improving data pipelines, training pipelines, deployment workflows, monitoring systems, and supporting infrastructure that allow the team to move faster and operate ML systems with confidence.
This is not a research-first role. It is best suited for someone who is excited by the systems, tooling, and operational side of machine learning.
What You'll Do
  • Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
  • Partner with researchers and ML practitioners to productionize models and enable faster iteration
  • Design, build, and improve data pipelines and training pipelines
  • Improve data processing, annotation workflows, and ML system efficiency
  • Deploy and maintain the background systems that support model training and inference
  • Build tooling and processes for monitoring model performance, system reliability, and operational health
  • Improve the scalability, observability, and reproducibility of ML systems
  • Optimize ML infrastructure for speed, reliability, and cost-efficiency
  • Identify bottlenecks in the ML workflow and automate or streamline manual processes
  • Help establish best practices around ML operations, deployment, and system performance

What You'll Bring
  • Several years of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments
  • Experience supporting ML systems end to end, from model handoff through deployment and monitoring
  • Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML
  • Experience working closely with researchers, data scientists, or ML practitioners to productionize models
  • Strong software engineering fundamentals and experience building production systems
  • Experience with monitoring, debugging, and improving production ML or data systems
  • A track record of improving reliability, scalability, speed, and/or cost efficiency in ML systems
  • Comfort operating in a fast-moving, startup-style environment with a high degree of ownership

Benefits + Perks
  • Competitive salary and equity in a high-growth startup
  • Flexible PTO, take what you need
  • Medical, dental, and vision coverage
  • Great startup culture, including company off-sites
  • High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more

An insight into our Core Values
Only the best belong here
We are unapologetic about talent. This should be the best team you have ever been on. Protecting that standard is how we honor each other's time, ambition, and craft.
We work even harder to keep our partners than we did to earn them initially
The work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.
We keep the patient downstream of every decision
At the end of the day, this is about the patient. We get there by deeply respecting and reflecting on our purpose: to develop software that aids teams in delivering better care.
Raise the bar on ownership
We grow because people here go beyond the minimum. We invest extra effort, care, and ownership into what we build.
The world is moving fast. We move faster.
This is a race. We work hard, we move early, and we stay ahead of problems and competitors. If we slow down, someone else will pass us.
Radical candor, zero politics
We say what's true, early, and we keep communication direct and clean so the team can move.
Bring good vibes and win together
We win as a team. We bring energy, support each other, and make the workplace somewhere people are excited to show up.
If this sounds like you, we'd love to have a chat!
#LI-Hybrid
About ExaCare AI
ExaCare AI is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, ExaCare AI powers more than 1,500 facilities, and is growing rapidly.
We recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!