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Deep Learning Quantization Jobs in Silver Spring, MD

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 · 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 · 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 ...

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Showing results 21-32

All JobsDeep Learning Quantization JobsDeep Learning Quantization Jobs in Silver Spring, MD

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 Aug 6, 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 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 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 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 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:
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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

URGENT NEED - AI/ML Subject Matter Expert (SME) ___________Baltimore, MD - ONSITE

Navtech, Inc.

Baltimore, MD • On-site

Full-time

Re-posted 21 days ago

Job description

I have an opportunity for "AI/ML Subject Matter Expert (SME) ___________Baltimore, MD - ONSITE" and I am looking for a candidate who can join Immediately if you are interested, reply to me with your updated resume or if you could refer someone I would really appreciate it.
Position : AI/ML Subject Matter Expert (SME)
Location : Baltimore, Maryland
Duration : long term Project
Job Description:
We are seeking AI/ML Subject Matter Experts (SMEs) with deep technical expertise to lead and drive innovation across critical projects. Ideal candidates will bring hands-on experience in AI/ML model development, deployment, and advanced research, particularly in secure and controlled environments.
Key Responsibilities:
  • Provide expert knowledge and leadership in the development and implementation of AI/ML solutions within the organization.
  • Stay updated with the latest trends in AI/ML and apply cutting-edge techniques to solve complex business challenges.
  • Act as a technical advisor and thought leader on AI/ML projects, guiding model design, development, and deployment.
  • Collaborate with cross-functional teams to gather requirements and build tailored AI/ML solutions.
  • Research, evaluate, and recommend new AI/ML technologies and methods for adoption.
  • Mentor and train junior team members on best practices and AI/ML technologies.
  • Lead the development, testing, and fine-tuning of AI/ML models ensuring performance meets organizational standards.
  • Ensure that AI-generated outputs cite original source documents to maintain transparency.

Special Project Requirements:
LLM Fine-Tuning:
  • Fine-tune pre-trained open-source LLMs, or simulate fine-tuning using adapters (LoRA) if compute resources are limited.

RAG Pipeline:
  • Implement Retrieval-Augmented Generation (RAG) pipelines to enhance LLM outputs with external data retrieval.
  • Employ Graph RAG techniques (multi-hop retrieval) for complex retrieval needs.

Deployment:
  • Host applications locally or simulate private cloud deployment.
  • No exposure of inference APIs to the public (simulate air-gapped environments if necessary).

Security Measures:
  • Encrypt all data storage and retrieval paths.
  • Simulate secure access measures like heartbeat monitoring or biometric authentication for highly secure apps.

API/Backend Development:
  • Provide REST APIs to enable access to LLM outputs and retrieval engines.

UI/UX:
  • Build a simple, intuitive user interface to demonstrate functionality and improve user experience.

Cost Awareness:
  • Demonstrate cost control strategies such as model quantization, optimized retrieval pipelines, and minimal GPU usage for efficiency.

Source Attribution:
  • Ensure every AI-generated answer cites its corresponding source documents for traceability.

Technical Skills Required:
  • Strong background in AI/ML and deep understanding of machine learning algorithms and techniques.
  • Proficiency in Python, R, or Java for AI/ML development.
  • Hands-on experience with LLMs, RAG pipelines, secure deployment practices, and API development.
  • Familiarity with cost-optimization methods for hosting AI solutions.

Regards,
Alex . K
NAVTECH INC
P : (224) 348-1340 E : Alex@navtechusa.com
1600 Golf Road. Suite 1200, Rolling Meadows, IL 60008
www.Navtechusa.com E-Verified Company.
Navtech logo

About Navtech

Sourced by ZipRecruiter

Industry

Civil engineering construction

Company size

11 - 50 Employees

Headquarters location

New Bloomfield, PA, US

Year founded

1996

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