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Machine Learning Engineer Quantization Jobs in Pennsylvania

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Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

They are seeking a Senior Machine Learning Engineer to develop and optimize machine learning models aimed at enhancing patient care and operational efficiency in hospital settings. Responsibilities ...

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

Vanguard Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

Bespoke Labs

Machine Learning Engineer

Indiana, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Bloomsburg, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Pittsburgh, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Reading, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Harrisburg, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Erie, PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Allentown, PA · On-site

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 ...

System One

Sr Machine Learning Engineer

Pittsburgh, PA · On-site

$101K - $139K/yr

Position Title: Sr Machine Learning Engineer Location: PA - Pittsburgh, TX - Dallas, OH - Cleveland Work Status : Onsite 5 days a week Duration : Contract to Hire Years Of Experience Required : 10+ ...

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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 job categories do people searching Machine Learning Engineer Quantization jobs in Pennsylvania look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Pennsylvania 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:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Pennsylvania as of July 2026, with employment types broken down into 85% Full Time, 9% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 85% Physical, 7% Hybrid, and 8% Remote job distribution.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Vanguard Group, Inc.

Malvern, PA • On-site

$102K - $140K/yr

Full-time

Posted 8 days ago

Vanguard rating

8.7

Company rating: 8.7 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

17th of 150 rated financial services

Job description

Core Responsibilities
  • Design, build, and maintain end-to-end machine learning pipelines from research through production deployment.
  • Engineer scalable training, inference, and retraining workflows using AWS SageMaker.
  • Develop and maintain feature engineering, feature storage, and data preparation pipelines.
  • Automate model deployment, testing, validation, and release processes using CI/CD practices.
  • Build batch, real-time, and event-driven architectures.
  • Implement model monitoring for performance, drift detection, data quality, and operational health.
  • Partner with quantitative researchers and data scientists to productionalize research models.
  • Manage model versioning, lineage tracking, experiment management, and reproducibility.
  • Optimize model performance, scalability, reliability, and cloud cost efficiency.
  • Establish engineering standards, testing frameworks, and governance controls for ML solutions.
  • Support production operations, incident response, and continuous improvement of deployed models.

Required Qualifications:
  • Minimum of eight years related work experience, with at least three years of development experience.
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
  • Experience in software engineering, machine learning engineering, data engineering, or a related technical discipline.
  • Strong experience building and deploying machine learning solutions in production environments.
  • Expertise in Python and modern data science libraries (Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, or similar).
  • Hands-on experience with AWS services, including SageMaker
  • Experience building and maintaining machine learning pipelines, feature engineering workflows, and model deployment processes.
  • Knowledge of MLOps practices, including CI/CD, model versioning, experiment tracking, monitoring, and automated retraining.
  • Strong understanding of software development lifecycle practices, testing strategies, and production support.
  • Ability to work effectively with researchers, data scientists, and business stakeholders to deliver business outcomes.

Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.
About Vanguard
At Vanguard, we don't just have a mission-we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

What Vanguard employees say

Pay

Benefits

Hours and flexibility

Workplace

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