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Machine Learning Engineer Quantization Jobs in Secaucus, NJ

Jane Street

Machine Learning Engineer

New York, NY

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Capital One

Lead Machine Learning Engineer

New York, NY · On-site +1

$112.10K - $147.70K/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

$112.10K - $147.70K/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 ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Kitware

Machine Learning Engineer

New York, NY · On-site

$85K - $125K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Virtu Financial

Machine Learning Engineer

New York, NY

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ

$127.90K - $168.60K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

Tagup

Machine Learning Engineer

New York, NY

$125K - $165K/yr

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems. In this role, you'll go beyond building models ...

DraftKings, Inc.

Senior Machine Learning Engineer

New York, NY · On-site

$114.30K - $157K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll join a team of algorithm experts and data science technologists building innovative data products that solve analytically complex ...

DraftKings

Senior Machine Learning Engineer

New York, NY

$114.30K - $157K/yr

The Crown Is Yours As a Senior Machine Learning Engineer, you'll join a team of algorithm experts and data science technologists building innovative data products that solve analytically complex ...

Attentive

Senior Machine Learning Engineer

New York, NY

$244K - $320K/yr

About the Role Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will ...

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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 May 31, 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 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 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 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 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? The top searched job categories for Machine Learning Engineer Quantization jobs in Secaucus, NJ are:
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
Infographic showing various Machine Learning Engineer Quantization job openings in Secaucus, NJ as of May 2026, with employment types broken down into 1% Internship, 56% Full Time, 40% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 87% Physical, 7% Hybrid, and 6% Remote job distribution, with an average salary of $130,917 per year, or $62.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Jane Street

New York, NY

Other

Posted 24 days ago

Job description

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform.

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use. 

We'll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches - whether it's neural networks, random forests, gradient-boosted trees, or sophisticated ensemble methods - to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modeling techniques, while also being able to break down the mathematics behind them.

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. While there isn't a fixed list of qualifications we're looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you'll fit right in. 

We're looking for someone with:

  • Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
  • A strong mathematical background; Good candidates will be excited about things like optimization theory, regularization techniques, linear algebra, and the like
  • A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
  • A proven ability to create and maintain an organized research codebase that produces robust, reproducible results while maintaining ease of use
  • Expertise wrangling an ML framework - we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow, or others
  • An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

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