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Machine Learning Engineer Quantization Jobs in Ewing, NJ

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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:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer[C2C/W2 ROLE]

SmartIPlace

Philadelphia, PA • On-site

Contractor

Re-posted 5 days ago

Job description

Job Title: Machine Learning Engineer [w2 role]

Location: Philadelphia, PA (Onsite – 4 days/week at 1800 Arch Street)
Alternate location: Reston, VA (for strong candidates)
Duration: Contract
Eligibility: USC, GC

Job Summary

We are seeking a hands-on Machine Learning Engineer with 5+ years of experience who can design, build, and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced, engineering-focused environment.

Key Responsibilities

  • Model Development: Design, build, train, and fine-tune machine learning and deep learning models for real-world use cases
  • Production Deployment: Deploy, monitor, and maintain ML models in production environments
  • Data Pipeline Development: Build and optimize scalable data pipelines for ingestion, transformation, and processing
  • Performance Optimization: Evaluate models using metrics like accuracy, recall, and AUC; optimize for performance and scalability
  • Collaboration: Work closely with cross-functional teams including data engineers, software engineers, and business stakeholders

Required Skills & Qualifications

  • 5+ years of experience as a Machine Learning Engineer or similar role
  • Strong Python programming skills with solid software engineering fundamentals
  • Recent and hands-on experience with PySpark (mandatory)
  • Experience with machine learning frameworks such as Scikit-learn
  • Strong understanding of statistics, probability, and algorithms
  • Experience working with SQL, data modeling, and large datasets
  • Proven track record of deploying ML models into production environments
  • Experience with AWS services

Preferred Qualifications

  • Experience with MLOps tools such as Docker for model deployment
  • Hands-on experience with local Large Language Models (LLMs)
  • Familiarity with distributed computing and big data technologies

Interview Process

Round 1 (30 mins – Virtual)

  • Experience overview
  • Technical discussion
  • Live coding exercise (Video ON + full desktop screen sharing required)

Round 2 (60 mins – In-Person Preferred)

  • Technical deep dive
  • Advanced live coding exercise

Work Environment

  • 4 days onsite preferred (Philadelphia office)
  • Open to relocation candidates
  • Reston, VA location may be considered if needed
Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

Social media

Facebook

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