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Machine Learning Engineer Quantization Jobs in Mount Royal, NJ

asrcfh

Senior Machine Learning Engineer

Moorestown, NJ

$103K - $141K/yr

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

Bespoke Labs

Machine Learning Engineer

Wilmington, DE · 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

West Chester, PA · 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

Philadelphia, PA · 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 ...

ASRC Federal

Senior Machine Learning Engineer

Moorestown, NJ · On-site

$103K - $141K/yr

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Mount Royal, NJ

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 Sep 14, 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 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 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 Quantization jobs near you

Senior Machine Learning Engineer

Moorestown, NJ

asrcfh
See more jobs at asrcfhexternal

$103K - $141K/yr

Full-time

Posted 11 days ago

ASRC Federal rating

7.8

Company rating: 7.8 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

Job description

ASRC Federal Mission Solutions is a premier provider of systems engineering, software engineering, system integration and project management services for real-time, mission-critical defense systems. We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ.

Responsibilities:

  • Develops, researches, and applies machine learning, deep learning, visual artificial intelligence algorithms and methods to data sets to produce models to be deployed in an operational aspect
  • Develops hypotheses based on data analysis and trends, and compares real-time results with predictions to update and fine-tune algorithms
  •  Develops assessment methods to ensure production models are robust and reliable
  • Collaborates with different business units and stakeholders
  • Develops, inspects, mines, transforms, and models data to raise productivity, improve decision making, and gain competitive advantage
  • Conducts quantitative and qualitative analysis on data to generate insights and information to ensure correct predictive forecasting or classification
  • Maintains analytical systems, verifies the accuracy of the data, and acts as liaison with business
  • Implementing emerging AI/ML solutions from commercial and academic domains to support military and government agencies with prediction, classification, and anomaly detection tasks
  • Evaluating, visualizing, and performing statistical analysis on data sets including time-series, multi-modal, and textual data
  • Training deep neural networks including MLPs, CNNs, Transformers, and others as required
  • Working with existing modeling and simulation (M&S) tools to develop data for new AI/ML models

Basic Qualifications:

  • Bachelor's degree and a minimum of 5-7 years of experience in a related or applicable field, or an equivalent combination of education and experience
  • This position requires the ability to obtain and maintain a government clearance, U.S. Citizenship is required
  • This position requires the successful applicant to obtain and maintain the required security clearance or other authorization(s) within the necessary timeframe required by applicable contract(s)
  • Requires advanced understanding and ability to apply standards, principles, theories, and technical concepts obtained through advanced education combined with experience
  • Has practical knowledge of project management
  • Works to achieve operational targets with significant impact on departmental results
  • Requires being responsible for managing entire technical projects within job area
  • Requires being responsible for developing technical solutions that may require collaboration with internal expertise and deep analysis of the technical system
  • Requires efficient communication with parties within and outside of own job function
  • Requires being responsible for communicating with parties external to ASRC Federal (e.g., customers, vendors, etc)  
  • Requires the ability to write and implement company policies pertaining to relevant technology
  • Responsible for running small technical teams while providing guidance, coaching and training to employees within job area
  • Lead projects, requiring the delegation of work and the review of others' work product
  • Basic knowledge of machine learning techniques including popular frameworks (e.g., PyTorch or TensorFlow)
  • Experience with LLM prompting and Transformer architecture

 

Preferred Qualifications:

  • Hands-on experience with PyTorch and related Python libraries
  • Experience with unsupervised learning including clustering algorithms and manifold learning
  • Strong writing and presentation skills are preferred

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