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Machine Learning Engineer Quantization Jobs in Englewood, CO

AppFolio

Principal Machine Learning Engineer

Denver, CO · On-site

Who We Are Looking For We're seeking a Principal Machine Learning Engineer to help define and lead the next generation of AI systems within Realm-X, and to drive AppFolio's long-term autonomous Real ...

AppFolio

Staff Machine Learning Engineer

Denver, CO · On-site

$200 - $250/hr

Production experience with model serving for LLMs and custom models, understanding quantization, batching, and routing. * Direct experience integrating with Google Vertex/Gemini, OpenAI, and ...

Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107K - $147K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building, maintaining, and monitoring the production ML models and offline experimentation frameworks that are ...

Cymertek Corporation

AI/ML Engineer

Aurora, CO · On-site

$110 - $160/hr

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, AI Research Scientist, Robotics ...

Cymertek

AI/ML Engineer

Aurora, CO · On-site

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist, Deep Learning Engineer, NLP Engineer, Computer Vision Engineer, AI Research Scientist, Robotics ...

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Showing results 21-40

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Englewood, CO

Machine Learning Engineer Quantization information

See Englewood, CO salary details

$31.1K

$127.2K

$191.1K

How much do machine learning engineer quantization jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning engineer quantization in Englewood, CO is $127,155.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,100.00 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Englewood, CO?

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What cities near Englewood, CO are hiring for Machine Learning Engineer Quantization jobs?

Cities near Englewood, CO with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer / Specialist

DCCA

Littleton, CO • On-site

Full-time

Re-posted 19 days ago

Job description

Machine Learning Engineer / Specialist
Location Littleton, CO
Job Code 2019
# of Openings 1

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