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Machine Learning Engineer Quantization Jobs in Pennsylvania

JOB SUMMARY Seeking a hands-on Machine Learning Engineer with strong Python programming expertise and recent PySpark experience to build, deploy, and support production-ready machine learning ...

Machine Learning Engineer, Data Mining

Pittsburgh, PA · On-site +1

$111K - $133K/yr

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain ... quantization) to ensure models run efficiently in production environments. * Data Mining & Analysis:

AI / Machine Learning Engineer (Contract) Location: Philadelphia, PA or Charlotte, NC Duration: 6 Months Contract Job Summary We are seeking an experienced AI / Machine Learning Engineer to design ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Machine Learning Engineer Quantization information

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 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 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Pennsylvania? For Machine Learning Engineer Quantization jobs in Pennsylvania, the most frequently searched job titles are:
What cities in Pennsylvania are hiring for Machine Learning Engineer Quantization jobs? Cities in Pennsylvania with the most Machine Learning Engineer Quantization job openings:
Infographic showing various Machine Learning Engineer Quantization job openings in Pennsylvania as of June 2026, with employment types broken down into 2% As Needed, 89% Full Time, 7% Part Time, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Compunnel

Philadelphia, PA • On-site

Contractor

Posted 3 days ago


Job description

JOB SUMMARY
Seeking a hands-on Machine Learning Engineer with strong Python programming expertise and recent PySpark experience to build, deploy, and support production-ready machine learning solutions. The ideal candidate should have experience deploying ML models into production, working with AWS cloud services, and setting up local LLM environments. This is an engineering role, not a management role. The hiring manager is specifically looking for someone who enjoys coding and solving technical problems.
Key Responsibilities
Design, develop, and deploy production-ready Machine Learning models
Develop scalable ML pipelines using Python and PySpark
Build and optimize ETL and data processing workflows
Work with AWS cloud services to support ML applications
Configure and work with Local LLM environments
Deploy Machine Learning models into production environments
Collaborate with software engineering teams to build scalable ML solutions
Troubleshoot, optimize, and maintain production ML pipelines
Required Qualifications
5+ years of Machine Learning Engineering experience
Extensive hands-on Python programming experience
Recent hands-on PySpark experience (Must Have)
Strong AWS cloud experience
Experience deploying Machine Learning models into Production (Must Have)
Strong coding and software engineering skills
Experience building scalable ML pipelines
Strong debugging and problem-solving skills
Preferred Qualifications
Experience setting up Local LLMs
MLOps experience
Distributed data processing experience
Model optimization and performance tuning
Experience with production AI/ML systems

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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