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Machine Learning Engineer Quantization Jobs in Chester, NJ

Xident B.V.

Senior Machine Learning Engineer

Union, NJ · On-site

$106K - $146K/yr

Senior Machine Learning Engineer We're looking for a Senior ML Engineer to advance our age bracket ... Experience with model optimization (quantization, pruning, distillation) for edge inference

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 · 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 ...

Bespoke Labs

Machine Learning Engineer

Edison, NJ

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Edison, NJ · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Paterson, NJ

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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

Machine Learning Engineer Quantization information

See Chester, NJ salary details

$33.4K

$136.4K

$204.9K

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 Chester, NJ is $136,385.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $164,200.00 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 cities near Chester, NJ are hiring for Machine Learning Engineer Quantization jobs?

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

Machine Learning Engineer Quantization jobs near you

Senior Machine Learning Engineer

Union, NJ • On-site

Xident B.V.
See more jobs at Xident B.V.external

$106K - $146K/yr

Other

Posted 11 days ago

Job description

Senior Machine Learning Engineer

We're looking for a Senior ML Engineer to advance our age bracket classifiers and face recognition models. We run 5 binary classifiers (+12/+15/+18/+21/+25) deployed as ONNX models for client-side inference via WebAssembly — you'll improve accuracy, reduce bias, and tackle anti-spoofing.

Xident is building the future of digital identity verification. Our platform enables businesses to verify users' ages and identities in seconds, while respecting privacy through our unique "Verify Once, Access Everywhere" model.

Founded in 2023, we've already processed over 10M+ verifications processed and serve 500+ businesses. We're a remote-first company with team members across 12 countries.

Our mission is simple: To make identity verification seamless, private, and accessible for everyone. We believe privacy and convenience shouldn't be mutually exclusive, and we're proving it every day.

25+

Team members

500+ businesses

Customers

12

Countries

What You'll Do
  • Improve our age bracket binary classifiers — currently +18 achieves 0.03% FPR / 11% FRR, target similar for +12/+15/+21/+25
  • Research and implement state-of-the-art face recognition using InsightFace (ArcFace) architectures
  • Develop robust liveness detection and anti-spoofing models resistant to photos, videos, and deepfakes
  • Optimize models for client-side ONNX Runtime inference (WebAssembly, Core ML, TensorFlow Lite)
  • Build fair and unbiased models — measure and mitigate demographic performance gaps
  • Collaborate with Python and Go engineers on training pipelines and model deployment via River queue
What We're Looking For
  • 7+ years of machine learning experience with focus on computer vision
  • Deep expertise in face recognition architectures (ArcFace, CosFace, or similar)
  • Strong PyTorch skills with experience exporting to ONNX for edge deployment
  • Published research or significant contributions to CV/ML projects
  • Experience with model optimization (quantization, pruning, distillation) for edge inference
  • Understanding of ML fairness, bias detection, and mitigation strategies
Nice to Have
  • PhD in Computer Science, ML, or related field
  • Experience with document OCR and VLM-based verification
  • Background in privacy-preserving ML — on-device inference, no server-side face storage
Our Values

We iterate quickly, gather feedback, and improve continuously.

Ownership Mentality

Everyone owns their domain end-to-end. No finger-pointing, just solutions.

Transparent by Default

We're happy to answer any questions before you apply. Reach out to our team anytime.

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