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Machine Learning Engineer Quantization Jobs in Secaucus, NJ

PhysicsX

Machine Learning Engineer

New York, NY · On-site

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking Machine Learning Engineers to build a platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of core technology and ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking Machine Learning Engineers to develop their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to various aspects such as ...

Apex Systems

Machine Learning Engineer

Jersey City, NJ · On-site

Job#: 3049321 Machine Learning Engineer Location Jersey City, New Jersey (Onsite) Employment Type Contract Contract Duration 12 Months Role Overview This position involves applying advanced machine ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · Hybrid

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site

$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

New York, NY

$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

Manhattan, NY

$112K - $148K/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

New York, NY · 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 ...

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Showing results 21-40

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Secaucus, NJ

Machine Learning Engineer Quantization information

See Secaucus, NJ salary details

$32K

$130.9K

$196.7K

How much do machine learning engineer quantization jobs pay per year?

As of Sep 14, 2026, the average yearly pay for machine learning engineer quantization in Secaucus, NJ is $130,917.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,200.00 and $157,600.00 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Secaucus, NJ?

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

What job categories do people searching Machine Learning Engineer Quantization jobs in Secaucus, NJ look for?

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What cities near Secaucus, NJ are hiring for Machine Learning Engineer Quantization jobs?

Cities near Secaucus, NJ with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

Manhattan, NY • On-site

Trading Interview
See more jobs at Trading Interviewexternal

Other

Posted 29 days ago

Job description

Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you’d like to learn more, you can have a look at our Machine Learning page .

During the program, you’ll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we’re still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.

The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including 1-2 dedicated to assessing ML engineering skills.

If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in. We don't expect you to have a background in finance—we're more interested in how you think and learn than what you currently know. You should be:

  • An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow
  • A top-notch programmer with a love for technology
  • Intellectually curious, collaborative, and eager to learn
  • Humble and unafraid to ask questions and admit mistakes

We were founded by a small group of traders and technologists in a tiny New York office. Today, we have more than 2,000 employees across five global offices. We trade...

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