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Machine Learning Engineer Quantization Jobs in Ewing, NJ

We are looking for a talented AI Solution Engineer to join our innovative team. This role involves ... Machine Learning: Proficiency in machine learning algorithms and techniques. Experience with ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Trenton, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

New Brunswick, NJ ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

AI Engineer

Philadelphia, PA ยท On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... using quantization, inference acceleration, and model-routing techniques - Designing agent ...

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior ML Ops Engineer

Philadelphia, PA ยท On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Senior Robotics AI Engineer

Philadelphia, PA ยท On-site

$160K - $180K/yr

We are seeking a Senior Robotics AI Enginee r with strong applied machine learning and robotics ... quantization, pruning and other model compression techniques. * Strong problem solving mindset and ...

Senior Robotics AI Engineer

Philadelphia, PA ยท On-site

$160K - $180K/yr

We are seeking a Senior Robotics AI Enginee r with strong applied machine learning and robotics ... quantization, pruning and other model compression techniques. * Strong problem solving mindset and ...

Showing results 21-40

Machine Learning Engineer Quantization information

See Ewing, NJ salary details

$30.2K

$123.5K

$185.6K

How much do machine learning engineer quantization jobs pay per year?

As of Sep 2, 2026, the average yearly pay for machine learning engineer quantization in Ewing, NJ is $123,523.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $148,700.00 per year, depending on experience, location, and employer.

What does a machine learning engineer quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What are some common challenges machine learning engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

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

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

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

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What cities near Ewing, NJ are hiring for Machine Learning Engineer Quantization jobs?

Cities near Ewing, NJ with the most Machine Learning Engineer Quantization job openings:

AI / Machine Learning Engineering Lead

Everest Re Group

Warren, NJ โ€ข Hybrid

$180K - $220K/yr

Full-time

Medical, Life, Retirement, PTO

This job post hasย expired 1 day ago.ย Applications are no longer accepted.


Job description

Title:

AI / Machine Learning Engineering Lead

Company:

Everest Reinsurance Company

Job Category:

Technology

Job Description:

About Everest:

Everest is a global leader in risk management, rooted in a rich, 50+ year heritage of enabling businesses to survive and thrive, and economies to function and flourish. We are underwriters of risk, growth, progress and opportunity. We are a global team focused on disciplined capital allocation and long-term value creation for all stakeholders, who care deeply about our impact on communities and the wider world.

About the Role:

We are looking for a talented AI Solution Engineer to join our innovative team. This role involves designing and implementing advanced AI models to solve complex business problems, particularly within the insurance sector. The ideal candidate will have a strong statistical background and be proficient in machine learning and data analysis.
This is a hybrid position based in Warren, NJ working 3 days onsite, 2 remote.

We are not considering fully remote candidates at this time.

Key Responsibilities:

  • Design and Develop AI Models: Create and implement AI models with a robust statistical foundation. Ensure models are scalable and can be integrated into existing systems.

  • Performance Evaluation: Develop and utilize metrics to evaluate the performance of AI models. Continuously monitor and refine models to maintain high performance and accuracy.

  • Data Analysis: Analyze large datasets to extract meaningful insights and patterns. Validate AI models against existing benchmarks and datasets.

  • Collaboration: Work closely with data scientists, software engineers, and other stakeholders to align AI solutions with business objectives. Communicate findings and recommendations to non-technical team members.

Skills Needed:

  • Machine Learning: Proficiency in machine learning algorithms and techniques. Experience with frameworks such as TensorFlow, PyTorch, or similar.

  • Statistical Analysis: Strong background in statistics and probability. Ability to apply statistical methods to real-world data.

  • Programming: Expertise in Python and/or R for data analysis and model development. Familiarity with SQL and other database technologies.

  • Data Analysis: Skilled in data preprocessing, cleaning, and transformation. Experience with data visualization tools to present findings effectively.

  • Insurance Domain Knowledge: Experience working with insurance datasets, including claims and underwriting data.

  • Understanding of industry-specific challenges and regulatory requirements.

Qualifications:

  • Education: A bachelor's degree in computer science, Statistics, Data Science, or a related field is required. A master's degree or relevant certifications (e.g., in machine learning or data science) are a plus.

  • Experience: 7-9 years of overall experience, including 3-5+ years in AI/ML development and deployment. Prior experience in the insurance industry is highly desirable.

  • Soft Skills: Strong problem-solving abilities, excellent communication skills, and the ability to work collaboratively in a team environment.

  • Adaptability: Ability to stay current with the latest AI trends and technologies and apply them to improve existing solutions.

The base salary range for this position is $180,000 - $220,000 annually. The offered rate of compensation will be based on individual education, experience, qualifications and work location. All offers include access to a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).
#LI-KG1

#LI-Hybrid

What if I don't meet every requirement? At Everest we are dedicated to building an inclusive and authentic workplace. So, if you are excited about this role but your past experience doesn't align perfectly with every element in the job description, we still encourage you to apply. You may be just the right candidate for this or other roles. Please let us know if you need any accommodations throughout the application or interview process.

Our Culture

At Everest, our purpose is to provide the world with protection. We help clients and businesses thrive, fuel global economies, and create sustainable value for our colleagues, shareholders and the communities that we serve. We also pride ourselves on having a unique and inclusive culture which is driven by a unified set of values and behaviors. Clickhereto learn more about our culture.

  • Our Valuesare the guiding principles that inform our decisions, actions and behaviors. They are an expression of our culture and an integral part of how we work: Talent. Thoughtful assumption of risk. Execution. Efficiency. Humility. Leadership. Collaboration. Inclusion and Belonging.
  • Our Colleague Behaviorsdefine how we operate and interact with each other no matter our location, level or function: Respect everyone. Pursue better. Lead by example. Own our outcomes. Win together.

All colleagues are held accountable to upholding and supporting our values and behaviors across the company. This includes day to day interactions with fellow colleagues, and the global communities we serve.

Type:

Regular

Time Type:

Full time

Primary Location:

Warren, NJ

Additional Locations:

Everest is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or creed, sex (including pregnancy), sexual orientation, gender identity or expression, national origin or ancestry, citizenship, genetics, physical or mental disability, age, marital status, civil union status, family or parental status, veteran status, or any other characteristic protected by law. As part of this commitment, Everest will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Everest Benefits at everestbenefits@everestglobal.com.

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