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Machine Learning Engineer Quantization Jobs in Massachusetts

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

Sr. Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Position Summary The Machine Learning Engineer will be responsible for the end-to-end development and deployment of Large language and machine learning models, with a primary focus on data ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

We are seeking a mid-level Machine Learning Engineer to help develop and scale RAG systems across the company. This is a hands-on, full-lifecycle ML role with a strong emphasis on retrieval models ...

Machine Learning Engineer

Woburn, MA · On-site

$115K - $140K/yr

The Role As a Machine Learning Engineer, you will help develop and integrate cutting-edge AI/ML models into production systems that solve critical national security problems. Working as part of a ...

Showing results 21-40

Machine Learning Engineer Quantization information

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 in Massachusetts are hiring for Machine Learning Engineer Quantization jobs?

Cities in Massachusetts with the most Machine Learning Engineer Quantization job openings:

Infographic showing various Machine Learning Engineer Quantization job openings in Massachusetts as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer - Hybrid

XPO

Boston, MA • On-site

$100K - $120K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 16 days ago


XPO rating

6.9

Company rating: 6.9 out of 10

Based on 227 frontline employees who took The Breakroom Quiz

233rd of 366 rated logistics


Job description

What you’ll need to succeed as a Machine Learning Engineer at XPO

Minimum qualifications:

  • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or military experience
  • 1 year of experience in software or machine learning engineering, including hands-on experience building data pipelines, ML infrastructure, or MLOps tooling
  • Experience developing data preparation, validation, or quality-checking tooling for machine learning pipelines
  • Proficiency in Python and SQL
  • Experience with cloud data or ML platforms (e.g., AWS, GCP, BigQuery)
  • Strong collaboration skills, with experience partnering with data science/applied science teams and data engineering teams

Preferred qualifications:

  • Master's degree in Computer Science or related field
  • 3+ years of experience building ML infrastructure for training, evaluation, and deployment at scale
  • Experience building and maintaining CI/CD pipelines for machine learning models
  • Experience with model serving and inference infrastructure (batch and real-time)
  • Experience implementing model monitoring, drift detection, and feedback-loop tooling
  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Experience partnering with data engineering teams on data pipeline reliability and access

 

About the Machine Learning Engineer job

Pay, benefits and more:

  • Competitive compensation package 
  • Full health insurance benefits available on day one 
  • Life and disability insurance 
  • Earn up to 15 days of PTO over your first year  
  • 9 paid company holidays 
  • 401(k) option with company match 
  • Education assistance 
  • Opportunity to participate in a company incentive plan

What you’ll do on a typical day:

  • Build and maintain data preparation and validation tooling to ensure high-quality inputs for ML and optimization models
  • Design and implement ML infrastructure for model training, evaluation, and deployment
  • Build and maintain CI/CD pipelines for machine learning models, including automated testing and validation
  • Implement model monitoring, drift detection, and feedback loops to track model performance in production
  • Partner with applied and data scientists to productionize models and streamline the path from experimentation to deployment
  • Collaborate with data engineering teams to ensure reliable, accessible data pipelines
  • Contribute to shared MLOps tooling and best practices across the AI/ML organization

Annual Salary Range: $100,000 to $120,000 Actual compensation may vary due to factors such as experience and skill set. This is an incentive-based position, which may include bonuses, incentive or commission plans.

About XPO

XPO is a top ten global provider of transportation services, with a highly integrated network of people, technology and physical assets. At XPO, we look for employees who like a challenge and can communicate effectively in all situations. We want to leverage your skills and years of experience to drive positive results while ensuring a bright future for yourself and XPO. If you’re looking for a growth opportunity, join us at XPO. 

We are proud to be an Equal Opportunity employer. Qualified applicants will receive consideration for employment without regard to race, sex, disability, veteran or other protected status.

All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test. 

The above statements are not an exhaustive list of all required responsibilities, duties and skills for this job classification. 

Review XPO's candidate privacy statement here.


What XPO employees say

Pay

Benefits

Hours and flexibility

Workplace

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About XPO

Sourced by ZipRecruiter

Founded in Greenwich, Connecticut, XPO Logistics, Inc., operating under the brand name XPO, is a one of the leading companies in the transportation and logistics sector. Operating its services in 30 countries, the company employs the use of ground-breaking technology in providing a broad suite of logistics services including supply chain management, freight brokerage, last mile logistics, and intermodal and drayage transportation. XPO's impressive history dates back to 2011 and within its relatively short existence, it has made a series of acquisitions to consolidate its top-notch range of services. Their mission is to provide outstanding results to customers by envisioning and implementing significant advancements in freight transportation and logistics.

Industry

Import-export

Company size

10,000+ Employees

Headquarters location

Greenwich, CT, US