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Machine Learning Engineer Quantization Jobs in Massachusetts

ICONSTAFF

Machine Learning Engineer

Cambridge, MA · On-site +1

Machine Learning Engineer - Computer Vision & Robotics Tycho.AI is redefining the future of ... CUDA kernel development and model optimization (quantization, pruning, distillation). * Experience ...

Cognex

Senior Machine Learning Engineer

Natick, MA · On-site

$115K - $225K/yr

Optimize neural networks for resourceconstrained environments (quantization, pruning, distillation ... Mentor junior engineers and champion engineering excellence in ML research and development.

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site +1

$144K - $192K/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:

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site

$144K - $192K/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:

Motional

Machine Learning Engineer, Data Mining

Boston, MA · On-site +1

$144K - $192K/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:

Sierra Ventures

Machine Learning Engineer

Somerville, MA · On-site

$170 - $200/hr

We're looking for a Senior Machine Learning Engineer to help advance the state of voice understanding at Modulate. In this role, you'll design, train, evaluate, and deploy cutting‑edge machine ...

SupportFinity™

Machine Learning Engineer

Boston, MA · On-site

$140 - $210/hr

About the Role We are seeking a high-impact Machine Learning Developer/Engineer to join our integrated discovery team. In this role, you will be the algorithmic engine of our programs, developing and ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

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. You ...

Capital One

Lead Machine Learning Engineer

Cambridge, MA · On-site +1

$112K - $147K/yr

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. You ...

Capital One

Lead Machine Learning Engineer (IC)

Cambridge, MA · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) 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.

Capital One

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.

C the Signs

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 ...

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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 are popular job titles related to Machine Learning Engineer Quantization jobs in Massachusetts?

For Machine Learning Engineer Quantization jobs in Massachusetts, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Massachusetts look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Massachusetts are:

What cities in Massachusetts are hiring for Machine Learning Engineer Quantization jobs?

Cities in Massachusetts 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 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

ICONSTAFF

Cambridge, MA • On-site, Remote

Full-time

Medical, Retirement

Re-posted 20 days ago

Job description

Machine Learning Engineer – Computer Vision & Robotics


Tycho.AI is redefining the future of autonomous intelligence. Spun out of MIT and backed by DoD contracts, we are building breakthrough AI and autonomy solutions for unmanned systems operating in GPS-denied and contested environments. We are a fast-growing, dual-use technology company at the forefront of national security and commercial innovation, with a mission to push the boundaries of what autonomous systems can achieve.

Joining Tycho.AI means being part of a team shaping the next decade of autonomy from defense applications to commercial opportunities in areas like logistics, disaster response, and beyond. If you want to work at the cutting edge of AI/ML and robotics with a company that’s poised for major impact and growth, we want to hear from you.


Responsibilities

  • Design, develop, and optimize ML models for computer vision and robotics tasks.
  • Build robust training and fine-tuning pipelines for large-scale datasets.
  • Integrate ML systems into real-world platforms, bridging research and production.
  • Write clean, efficient, and maintainable code across Python and/or C++.
  • Stay current on research and apply state-of-the-art techniques in autonomy and perception.


Requirements

  • Bachelor’s or advanced degree in Computer Science, Engineering, or related field.
  • Hands-on experience applying ML to computer vision and/or robotics.
  • Proficiency with PyTorch or TensorFlow.
  • Strong coding skills in Python or C++ (ideally both).
  • Experience deploying ML models and building training pipelines.
  • Familiarity with Git and collaborative software development practices.


Nice to Have:

  • CUDA kernel development and model optimization (quantization, pruning, distillation).
  • Experience with ONNX, TensorRT, or OpenVINO for deployment.
  • Robotics middleware (ROS2).
  • SLAM, 3D perception, or sensor fusion (LiDAR, IMU).
  • Real-time or low-latency inference pipelines.


Why Tycho.AI

  • Be part of a rapidly scaling startup defining the future of autonomous intelligence.
  • Collaborate with top engineers and researchers from MIT, Google, and across the defense innovation ecosystem.
  • Direct impact on national security missions and dual-use commercial applications.
  • Along with a competitive salary and options, Tycho.AI offer a robust benefits package, including many options from medical insurance with 80% company contribution to pet insurance and a 401(k) retirement plan.