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Machine Learning Engineer Quantization Jobs in Mount Royal, NJ

Machine Learning Engineer Philadelphia, PA OR Washington, DC | Hybrid: 3-4 days/week 9 + Months Role: Design and validate ML models that support engineering tooling teams. Enhance existing AIML ...

Machine Learning Engineer 3-7881

Philadelphia, PA ยท On-site +1

$115.50K - $138.70K/yr

... both software engineering and machine learning sides of projects by implementing, rening, and validating machine learning algorithms for products and applications; take action on existing ...

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Machine Learning Engineer Quantization information

See Mount Royal, NJ salary details

$30K

$122.8K

$184.5K

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 Mount Royal, NJ is $122,775.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,800.00 and $147,800.00 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 cities near Mount Royal, NJ are hiring for Machine Learning Engineer Quantization jobs? Cities near Mount Royal, NJ with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer

Guru Schools

Philadelphia, PA โ€ข On-site

Full-time

Posted 29 days ago


Job description

Overview:
Machine Learning Engineer
Philadelphia, PA OR Washington, DC | Hybrid: 3-4 days/week
9 + Months
Role:

Design and validate ML models that support engineering tooling teams.
Enhance existing AIML automation tools (e.g., Speech data), implement LLM prompt interactions, and use LLMs to test LLMs - with a strong focus on product quality.
Key Responsibilities:
Build & enhance ML/AI models for validation and automation
Implement prompt-based LLM interactions
Collaborate across tooling squads and cross-functional teams
Contribute to POC development in AI/ML & Computer Vision
Requirements:
4+ years overall experience
1+ year hands-on ML model experience
Strong quality-focused mindset with LLM expertise
NLP, data engineering & model deployment experience
Tech Used:
GPT, LLMs, NLP, internet-developed tools
Interview Process:
2 Rounds
Skills:
Design and validate ML models that support engineering tooling teams. Enhance existing AIML automation tools (e.g., Speech data), implement LLM prompt interactions, and use LLMs to test LLMs