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Machine Learning Engineer Quantization Jobs in Brooklyn, NY

Machine Learning Engineer

New York, NY ยท On-site

$148K - $212K/yr

We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with ...

Machine Learning Engineer

New York, NY ยท On-site +1

$148K - $212K/yr

We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with ...

Treeswift is seeking a highly skilled and motivated engineer to join our team. You will play a pivotal role in developing and deploying state-of-the-art machine learning solutions to advance our ...

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 ...

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 ...

Lead Machine Learning Engineer

New York, NY ยท 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 ...

Lead Machine Learning Engineer

New York, NY ยท 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 ...

Lead Machine Learning Engineer

New York, NY ยท 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 ...

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 ...

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 ...

Machine Learning Engineer

New York, NY ยท 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 ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Senior Machine Learning Engineer Button's mission is to empower the companies shaping the creator and affiliate economy - fueling mobile growth with innovation and new paths to monetization. Today ...

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

The CreativeX RAPID (Real-time Ad Personalization & Insights Development) team is seeking passionate and talented Machine Learning Engineer to join us. CreativeX is on a mission to enable brands of ...

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Showing results 1-20

Machine Learning Engineer Quantization information

See Brooklyn, NY salary details

$33.1K

$135.4K

$203.5K

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

As of Jun 16, 2026, the average yearly pay for machine learning engineer quantization in Brooklyn, NY is $135,401.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $163,000.00 per year, depending on experience, location, and employer.

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 Brooklyn, NY? For Machine Learning Engineer Quantization jobs in Brooklyn, NY, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Brooklyn, NY look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Brooklyn, NY are:
What cities near Brooklyn, NY are hiring for Machine Learning Engineer Quantization jobs? Cities near Brooklyn, NY with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer

Spotify

New York, NY โ€ข On-site

$148K - $212K/yr

Other

Medical, Retirement, PTO

Posted 7 days ago


Job description

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them.ย 
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We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with Spotify - and who make impactful changes to Home recommendation systems to achieve this goal. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction.
What You'll Do
  • Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
  • Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
  • Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
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Who You Are
  • You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
  • You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
  • You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
  • Experience with PyTorch, Ray, Hugging Face and related tools is required.
  • You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
  • You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
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Where You'll Be
  • We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
  • This team operates within the Eastern Standard time zone for collaboration.
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The United States base range for this position is $148,000 $212,000 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens.
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At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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