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Deep Learning Quantization Jobs in Silver Spring, MD

Markon

Data Scientist Level 4

Fort George G Meade, MD · On-site

$220K - $235K/yr

Deep understanding of machine learning architectures, model selection, training, and optimization ... Strong background in AI/ML performance optimization, including model compression, quantization, or ...

Markon

Data Scientist Level 4

Fort George G Meade, MD

$220K - $235K/yr

Deep understanding of machine learning architectures, model selection, training, and optimization ... Strong background in AI/ML performance optimization, including model compression, quantization, or ...

Markon

Data Scientist Level 4

Fort George G Meade, MD · On-site

$220K - $235K/yr

Deep understanding of machine learning architectures, model selection, training, and optimization ... Strong background in AI/ML performance optimization, including model compression, quantization, or ...

Entarian

MLOps Engineer

Arlington, VA

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

Entarian

MLOps Engineer

Arlington, VA · On-site

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

Entarian

MLOps Engineer

Arlington, VA

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

Entarian

MLOps Engineer

Arlington, VA

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

Entarian

MLOps Engineer

Arlington, VA

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

Entarian

MLOps Engineer

Arlington, VA

Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ... Optimize models for production (e.g., via quantization or pruning) and ensure efficient resource ...

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Deep Learning Quantization information

See Silver Spring, MD salary details

$11.4K

$86.7K

$144.7K

How much do deep learning quantization jobs pay per year?

As of Jun 1, 2026, the average yearly pay for deep learning quantization in Silver Spring, MD is $86,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,400.00 and $143,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Quantization Engineer, and why are they important?

To excel as a Deep Learning Quantization Engineer, you need a strong background in machine learning, applied mathematics, and computer science, usually supported by an advanced degree in a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), quantization toolkits, and hardware acceleration platforms is crucial. Analytical thinking, problem-solving, and clear technical communication are standout soft skills in this role. These abilities are essential for efficiently optimizing models for deployment on resource-constrained hardware while maintaining accuracy and performance.

What are some common challenges faced when implementing deep learning quantization in production environments?

One of the main challenges in implementing deep learning quantization is balancing model accuracy with computational efficiency, as quantization can sometimes lead to a drop in model performance. Additionally, ensuring hardware compatibility and optimizing for different devices (such as CPUs, GPUs, or edge devices) can require extensive testing and tuning. Collaboration with data scientists, software engineers, and hardware specialists is often essential to successfully deploy quantized models at scale. Staying updated with the latest quantization techniques and frameworks is also important for overcoming these challenges.

What is deep learning quantization?

Deep learning quantization is the process of reducing the precision of the numbers used to represent a neural network's parameters, activations, or both. By converting the typically used 32-bit floating-point values to lower bit-width formats such as 16-bit or 8-bit integers, quantization significantly reduces the memory footprint and computational requirements of deep learning models. This technique helps deploy models efficiently on edge devices and mobile hardware while maintaining acceptable accuracy levels. Quantization is widely used in model optimization for faster inference and lower power consumption.

What is the difference between Deep Learning Quantization vs Machine Learning Engineer?

AspectDeep Learning QuantizationMachine Learning Engineer
Required CredentialsAdvanced degrees in AI, Computer Science, or related fields; knowledge of neural networksBachelor's or Master's in CS, Data Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, hardware optimization settingsSoftware development teams, data-driven projects, product-focused environments
Industry UsageAI hardware optimization, model deployment, edge computingModel development, data analysis, software solutions across industries

Deep Learning Quantization focuses on reducing model size and improving inference speed through techniques like weight and activation quantization, often in hardware or embedded systems. Machine Learning Engineers develop, implement, and optimize machine learning models for various applications. While both roles require knowledge of AI and programming, Deep Learning Quantization is more specialized in model optimization techniques, whereas Machine Learning Engineers work broadly on model development and deployment.

What are popular job titles related to Deep Learning Quantization jobs in Silver Spring, MD? For Deep Learning Quantization jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Deep Learning Quantization jobs in Silver Spring, MD look for? The top searched job categories for Deep Learning Quantization jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Deep Learning Quantization jobs? Cities near Silver Spring, MD with the most Deep Learning Quantization job openings:
Deep Learning Quantization jobs near you
ME00592-Data Scientist 4

ME00592-Data Scientist 4

Momentum Engineering, Inc.

Fort George G Meade, MD • On-site

$165K - $215K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 28 days ago

Job description

Momentum Engineering, Inc. fosters an employee-centric culture. Our strength lies in our people. With a high percentage of employees holding advanced degrees in engineering, computer science, and related disciplines, we bring deep technical expertise to every mission. Our team includes professionals with security clearances and full-scope polygraphs, ensuring trusted, secure support for the most sensitive national security initiatives. Additionally, our workforce is equipped with industry-leading certifications, demonstrating a commitment to continuous learning and excellence. Most importantly, our exceptional employee retention rate reflects a culture of professional growth, mission focus, and dedication-ensuring long-term stability and expertise for our customers' critical needs.
Job Summary
  • Seeking a Data Scientist to support advanced analytics and artificial intelligence initiatives within the MPO customer environment, designing and implementing sophisticated AI/ML solutions across multiple mission domains
  • This role focuses on developing scalable, high-performance models, including Agentic AI systems and Retrieval Augmented Generation (RAG) capabilities, to enable intelligent automation and data-driven decision-making
  • The ideal candidate brings deep expertise in machine learning, model optimization, and deploying AI solutions in constrained environments, with a strong ability to select and tailor models for mission-specific use cases

Primary Responsibilities
  • Design, develop, and implement advanced AI/ML and data science solutions across mission-focused domains
  • Architect and deploy Agentic AI systems and customized RAG (Retrieval Augmented Generation) solutions
  • Evaluate, select, and optimize machine learning models to meet specific mission requirements and performance constraints
  • Develop, train, fine-tune, and validate LLMs and other ML models, ensuring accuracy, efficiency, and scalability
  • Optimize models for deployment in low-memory, low-resource (edge) environments
  • Build and maintain data pipelines and model workflows to support continuous learning and improvement
  • Conduct model performance evaluation, including testing, validation, and tuning for optimal outcomes
  • Collaborate with stakeholders to translate mission needs into AI-driven solutions
  • Stay current with emerging AI/ML technologies, frameworks, and best practices
  • Document methodologies, architectures, and results to support repeatability and knowledge sharing

Required Qualifications
  • Must have active Top Secret/SCI clearance with NSA Full Scope Polygraph
  • Master's Degree with 9 years of relevant experience, Bachelor's Degree with 11 years of relevant experience, Associate's Degree with 13 years of in-depth relevant experience that is clearly related to the position
  • Expert proficiency in Python for AI/ML development
  • Demonstrated experience designing and implementing advanced AI/ML solutions
  • Experience with Agentic AI architectures and RAG-based systems
  • Strong background in machine learning model development, training, and optimization (including LLMs)
  • Experience deploying models in resource-constrained or edge environments
  • Ability to evaluate and select appropriate ML models based on mission requirements
  • Strong analytical, problem-solving, and system design skills

Desired Qualifications
  • Experience within MPO or Intelligence Community environments
  • Familiarity with distributed systems, cloud, or hybrid AI architectures
  • Experience with model performance tuning, compression, or quantization techniques
  • Knowledge of data engineering pipelines and large-scale data processing
  • Experience integrating AI solutions into operational systems and workflows

Exempt hourly position. 11 paid holidays, minimum of 3 weeks PTO, company sponsored group medical plan, company paid dental, vision, life insurance, and STD/LTD plans. Salary is dependent upon the candidate's experience and qualifications.
The pay range for this role is:
165,000 - 215,000 USD per year (Ft. Meade MD)

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