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Machine Learning Engineer Jobs in Pennington, NJ

Toogeza

Senior Machine Learning Engineer

Philadelphia, PA

$105K - $144K/yr

Clearly communicate complex technical concepts to non-engineering stakeholders in an accessible, outcome-focused way. What we're looking for An MS or PhD in Computer Science, Machine Learning ...

Comcast

Machine Learning Engineer 3-7881

Philadelphia, PA · On-site +1

$115K - $138K/yr

... both software engineering and machine learning sides of projects by implementing, rening, and validating machine learning algorithms for products and applications; take action on existing ...

Omni Inclusive

ML/AI Engineer

Princeton, NJ · On-site

Machine Learning Engineer Design, develop, and implement machine learning and deep learning models. Preprocess and analyze large-scale structured and unstructured datasets. Optimize models for ...

Vangard, Inc.

Senior AI/ML Engineer

Philadelphia, PA · On-site

$105K - $144K/yr

We are seeking an experienced Senior Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Pennington, NJ

Machine Learning Engineer information

See Pennington, NJ salary details

$31.8K

$130K

$195.3K

How much do machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer in Pennington, NJ is $129,969.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $156,400.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What cities near Pennington, NJ are hiring for Machine Learning Engineer jobs? Cities near Pennington, NJ with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Pennington, NJ as of May 2026, with employment types broken down into 1% Internship, 54% Full Time, 43% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $129,969 per year, or $62.5 per hour.

Senior Machine Learning Engineer

Toogeza

Philadelphia, PA

$105K - $144K/yr

Other

Posted 20 days ago

Job description

Opportunity Description

This is an opportunity to join a data-rich technology leader with a combined audience of hundreds of millions of players worldwide. We're building an Ad Network, leveraging best-in-class industry solutions to unite supply and demand intelligently in underserved digital segments.

Our platform is powered by unique access to rich first-party user data derived from our massive owned audience, which gives us an undeniable edge in delivering superior user profiling and higher-performing campaigns.

We are initially focused on dominating the high-value iGaming vertical, leveraging this data advantage, with a clear strategic goal of rapidly scaling into other lucrative segments, such as Forex and beyond. You'll work alongside a leadership team with deep experience from top big tech companies and industry-leading ad platforms, stepping into a pivotal role that offers the chance to define the foundational architecture and deliver immediate, massive impact on a globally scaled product.

What You'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems. Build and refine systems for creative understanding and user behaviour modelling, enabling more accurate and context-aware engagement predictions. Responsible for model quality and reliability by monitoring performance, calibrating predictions, and proactively addressing data drift and delayed feedback. Clearly communicate complex technical concepts to non-engineering stakeholders in an accessible, outcome-focused way.

What we're looking for

An MS or PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent practical experience. Over 3 years of hands-on experience developing and operating large-scale ad delivery and optimization systems. Experience working with CTR/CVR modeling, creative or content understanding, or user behavior modeling. Strong proficiency in general-purpose programming languages such as Python, Go, Scala, C++, or similar. A solid grasp of metric design, experimentation methodologies like A/B testing, and large-scale data processing and analysis

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