1

Machine Learning Engineer Quantization Jobs in Seattle, WA

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

Applied Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and ...

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

We're looking for an exceptional Machine Learning Engineer to help shape the future of our core platforms, products, and customer experiences. FinTech is one of the most complex and rapidly evolving ...

Machine Learning Engineer

Seattle, WA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

As a Machine Learning Engineer, you will design and maintain AI solutions for customer support, collaborating with a team to enhance SAP's support offerings. Responsibilities : • Design, train, and ...

Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan the project milestones, resourcing and work distribution * Execute ...

Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan the project milestones, resourcing and work distribution * Execute ...

Machine Learning Engineer

Seattle, WA · On-site

$93K - $125K/yr

We are looking for a Machine Learning Engineer to join our team of driven machine learning and software engineers. This role covers system design, prompt engineering, ML model evaluation, building ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

See Seattle, WA salary details

$35.8K

$146.5K

$220.2K

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

As of Jul 6, 2026, the average yearly pay for machine learning engineer quantization in Seattle, WA is $146,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $176,400.00 per year, depending on experience, location, and employer.

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 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 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 Seattle, WA? For Machine Learning Engineer Quantization jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Seattle, WA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Seattle, WA are:

Machine Learning Engineer

Constellation Space

Seattle, WA • On-site

$120K - $180K/yr

Full-time

Posted 6 days ago


Job description

The Role

We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that directly impact Constellation’s orbital systems and ground operations.

Responsibilities

  • Deploy, monitor, and maintain ML models in production environments.

  • Build robust MLOps pipelines for continuous training and integration of models using telemetry data.

  • Optimize algorithms for low-latency inference on edge devices (spacecraft hardware).

  • Collaborate with data scientists and flight software engineers to integrate AI capabilities into core flight systems.

Requirements

  • B.S. or M.S. in Computer Science, Engineering, or equivalent experience.

  • Proven experience deploying machine learning models into production.

  • Strong software engineering skills in Python and C++.

  • Experience with cloud platforms, containerization (Docker), and MLOps tools.

Compensation Range: $120K - $180K